We should be honest about the game. The game is surely fun, but addictive. People can have pleasure and satisfaction after the game but also regret the time they have spent on it. So, human beings can feel very ambivalent about games.

I think that gamification in the education field can be understood and explained by the educational philosophy of John Dewey. At first, philosophy starts with definitions of concepts. Human beings think through language. Defining the meaning of words in detail can be the foundation to share and expand thoughts with others.

So, Why John Dewey? Dewey created the basic framework of modern education. His concepts are familiar to Korean people, through many books and thoughts related to the concept of educational philosophy. His representative book, ‘Democracy and Education’, illustrates educational concepts including interaction, continuity, interest, growth, and experience. All of these concepts can be considered part of what we call gamification.

Continuity

Continuity is an important principle of gamification. Human life is based on continuity. As we live our lives, many things change, but many things also remain the same. Human beings live through the flow of time and are subject to the influence of continuity.

Many games seek to facilitate continuity. Games on Nintendo or PlayStation, for example, allow you to save your progress and reload after a break in playing. These functions maintain continuity, which encourages the player to keep playing. If a game is a short-term and one-time experience, the effects of the game on human beings are not great or lasting. A game which one plays for a long time, has a much greater impact. Each game has its own objective, but some games have continuity as an objective. These games continue without ending or have finite but long-term objectives. This characteristic is one of the gamification principles, and has an important role in creating the fun of the game.

Interaction

Interaction is a very old philosophical concept, and includes all activities concerning moving and reacting with others, and external objects. Movies, cartoons, or works of art don’t interact with us. On the other hand, a game is a complex thing with interaction. By clicking, touching, or choosing in the game, the player receives constant feedback. This interaction can make the player immersed in the game.

Human beings live through communication. We continuously interact with others. This is fundamental to our existence, and good and free interaction makes life abundant and interesting. One important principle of gamification is well-designed interaction. Dewey himself mentioned that education is interaction, and this is the core of gamification. Every life is not being alone but interacting with others.

Interest

Dewey explained ‘Interest’ through the story of bystanders and actors in his book ‘Democracy and Education’. In some events, a bystander with no interest and an actor will differ greatly in the results they achieve. Interest is not just in short-term reward and stimulus but in continuous self-will. Continuous interest makes human life abundant and is empowering. If there is no interest, a person loses power (to act) and doesn’t develop. This is the loss of desire to act. Gamification can stimulate human desire to act by stimulating interest. Therefore, interest is one concept which can separate games from other works. Normally, the reason why people play games is to have ‘fun’. The necessary concept in gamification, which occasions this is ‘interest’.

Growth

In Dewey’s perspective, education is the activity of seeking growth. If there is no growth through education, education is no longer required. Education can be the core for growth. Not just the growth of the physical body but internal growth and maturity is the key to education. Dewey thought that growth is a process towards completion. Games also have this process of progress from easy levels to more difficult ones. The principle of growth is applied. In the past, the Tamagotchi game in the past consisted of activities to grow and develop virtual animals. The reason why many people love this is the growth of characters in the game. If there is no growth, there is no life, and it is no longer fun for humans.

Growth is also very important in gamification. Particularly if it is used for educational purposes, growth should be more focused on development. Growth through games can be a process of seeking ‘the truth’ or developing (in-game) skills, or gaining information and knowledge. This is education. A game for learning or study has steps, and a process which leads the player’s learning. If it leads to growth, it can be named as education, in which case, there is a blurring of the purposes of the game and the learning.

Experience

Experience can be defined as an ‘overall ending achieved’. This ending includes all ‘Beginning – Development – Achievement’ processes that have been part of the experience. For example, every detailed story in a game includes background music and background story, historical facts, and many other ideas.

The main characters in the game are constructed from many historical, and cconceptual materials, such as the languages used, the type of speech is used, their relationships, the clothes and foods depicted, etc, not just their (game) objectives. For players who see, hear, and experience it, the process itself can be an educational experience. The education experience is a complete with continuous interaction, interests, and growth.

When we see research about immersion related to gamification, we can see that gamification helps to create better educational experience. Immersion is very important for learning, and games can give bigger immersion than other activities. Immersion into games by children allows tremendous depth of experience. Immersion means that a human deeply dives into some activities, and that their current experience can be felt as optimal. These immersive experiences can also be educational experiences. For immersion, ‘Objective, Competition, Interaction’ is required.

Human live their lives through experience, and life is the continuous process of many experiences. In addition, the educational experience is meaningful. If games are used to present ethical and artistic experiences, gamification can be extended into really meaningful areas of human life. If this kind of educational experience is continued, it can become a life habit. And it can be accessible for all. As requirement to learn and access educational experiences grow, the requirement for gamification will grow too. These experiences will lead to making human life abundant. The principles of gamification meet the major concepts of educational philosophy.

The post Gamification and John Dewey first appeared on Ludogogy.

Probably the most well-known theorist / writer on the topic of Flow was Mihaly Csikszentmihalyi, the Hungarian American Psychologist who died in October 2021. He worked in the fields of Creativity and Happiness and was the author of the book, ‘Flow: the Psychology of Optimal Experience’.

Flow: The Psychology of Optimal Experience is available on Amazon

It is likely that you will hear people referring to ‘flow’ both as a state of optimal concentration on a particular activity, and the experience of being in that state. Those who experience flow describe it as a state of complete absorption, where any external concerns, including time, the needs of the body, and so on, fall away. Many refer to it as being ‘in the zone’, and report feeling very skilled at what they are doing, where one action leads to the next seemingly effortlessly.

Csikszentmihalyi posited that three conditions contribute to the flow state.

The balance between the perception of the challenges of the tasks and perception of one’s ability to perform it. In other words, the task must lie in a perceived ‘Goldilocks Zone’ where it is neither too easy (which would break absorption through boredom) or too difficult (which would bring about the frustration of failure).

Clear goals which help to establish the structure of the activity and to indicate progress

Clear and immediate feedback helps to maintain flow by measuring progress towards goals and allowing swift adjustment to performance.

The first of these is often seen as the most important because, if the perception of challenge is well-designed for, that will necessarily include clear goals and feedback.

In addition to the feeling of absorption and perception of achievement, flow experiences are also characterised by a feeling of being in control and loss of reflective self-awareness.

Flow requires active participation, so passive activities such as watching television will not elicit a flow experience. Given that Csikszentmihalyi believed that flow experiences contributed to overall life satisfaction, this has deep implications in fields like education and learning (passive vs experiential learning methods), and design of workplace activities, both of which Csikszentmihalyi was interested in.

Other researchers have applied his work to other fields including music, sport, games and play and the workplace. It is important to note that beyond the positive feelings experienced by people ‘in flow’, the state is also associated with persistence and high achievement, so it is seen as a beneficial characteristic to design for.

Flow in Learning

The balancing of skills with challenge is consistent with a number of other theories and practices in education and learning. For example, the practice of ‘scaffolding’, where new learning is built on a basis of previous learning is very consistent with keeping a learner in flow as their perception of complexity (of the task) and their own skills can move forward at a similar pace towards a well-defined goal.

Likewise, one of the intentions of ‘differentiation’ is to match learning to the needs and capabilities of learners, which would also serve to maximise the potential for flow-creating situations. This can also be a way to ensure ‘relevance’ to learners which is one of the requirements of the Andragogy theory of Malcolm Knowles – the level at which someone is operating within their n a workplace task, would be an aspect of the relevance of learning to their life/work.

Flow is obviously, within itself, a rewarding state, which learners are motivated to achieve, so designing for flow is an effective way to keep learners engaged in learning. It is often cited as a reason for using games in learning, because well-designed games are engines for flow.

Flow in Games and Play

Games establish clear goals through their winning conditions, as well as smaller sub goals that players must carry out in order to progress within the game.

Well-designed games make is easy for players to understand how well they are doing within the context of the game, and to adjust their actions to play ‘better’, by feeding back on player actions through mechanisms such as scoring or position.  For example, when pieces are taken in Chess, a player can see how they are doing in comparison to their opponent by how much ‘material’ they each have remaining. They can also see from the position of the pieces on the board, whether they threaten or are threatened and the capability of different pieces to influence the game.

Through the above, players take part in learning which progressively improves their ability to play. So long as the game is not seen as ‘too difficult’, or ‘too easy’, the matching of perceived ability and challenge will keep the player in flow. This may of course involve matching oneself to opponents who provide the right level of challenge, or applying a ‘handicap’ to level the game for players of differing abilities. The benefits achieved can be self-perpetuating, because the challenges of learning to play can keep the player in flow, meaning they wish to continue to play, meaning they continue to learn.

The post Flow Theory in Games and Learning first appeared on Ludogogy.

Building Blocks of Tabletop Game Design is available on Amazon

I’m not sure whether I would have foregone that piece of work, if this book by Geoff Engelstein and Isaac Shalev had existed back then, because it was extremely instructive, but I would definitely have used the book as a starting point for my exploration of game mechanics.

Simply put, this book is an invaluable resource for any game designer, and I have found myself dipping into almost daily since I got it. Like the best sourcebooks it is easy to find what you require. The mechanics are categorised into chapters, by the purpose they serve inside a game and each mechanism is referenced by an id which indicates its category and order within the chapter – which I have found useful as a shortcut to reference them within game design documentation.

The impossibility of listing all game mechanics

While, as any game designer knows, there is often ambiguity about what category any specific mechanism should fit into, I think the authors have done an excellent job both in categorising a mechanic by its primary effect or purpose and in selecting the categories they will include in the book.  There are 13 chapters each with between 10 and 20ish mechanics, ranging from the very broad  – Chapter One is entitled ‘Game Structure’ and the very specific – Chapter 10 deals with ‘Movement’.

So, this is not intended to be an exhaustive list of all mechanics. This, in any case, would be an impossible task. Take for example STR-10 (Game Structure mechanic 10) – Legacy Games. A few years ago this term had not been coined. New mechanics are being discovered or invented all the time. In the introduction to the book the authors state where the lines have been drawn. First and most obviously, the title suggests that we are looking at the mechanics of tabletop games, but even within that, they state that e.g. wargaming, miniatures gaming and classic and collectible card games are only referenced in passing, and that whole categories such as narrative, dexterity and pantomime are equally lightly touched upon.  Maybe these will form the basis of a further book, or furnish an opportunity for other authors to produce a similarly comprehensive work.

My very favourite thing about this book, are the discussions of each mechanic. Each mechanic is illustrated with a line graphic which visualises its effect neatly, a short description which explains the effect of the mechanic, and then the discussion, which demonstrates the mechanic in action in real games, so you can find out, for example, how Loans (ECO-07) work in Railway Tycoon or Wealth of Nations, or how Push-Your-Luck operates in Can’t Stop or Mystic Vale.  Each mechanic section ends with a list of sample games which demonstrate the use of the specific mechanic.

Useful index for game design

At the rear of the book is the game index. This allows you to look up a game and see which mechanics it features. For example, when looking up Chess you will find ARC-06 – Force Projection, ECO-11 – Upgrades, MOV-01 – Tessellation, MOV-03 – Pattern Movement, RES-11 – Static Capture and STR-01 – Competitive Games.

Eric Zimmermann, who wrote the foreword for the book, mentions some points that are worth raising here too.  While some may feel that the 184 mechanisms listed in the book are just a small fraction of those that exist, the categories that are included are treated with depth, for example there are now fewer than 16 different Auction mechanics – which brings me to one final point.

While these are game mechanics, the ideas they represent have application outside of games too -questions of fairness, communication and determining winners in a given situation amongst other things are illuminated by study of these games.

And far from ruining a thing by examining it too closely, reading this book can enrich your play too, even if you have no intention of ever designing a game yourself. Next time you play, your appreciation of a game will be enhanced by a greater understanding of how a mechanic is operating, and the care and thought that a designer has applied to make your experience just so.

Building Blocks of Tabletop Game Design is available on Amazon

The post Review of Building Blocks of Tabletop Game Design first appeared on Ludogogy.

So it’s wonderful to come across a book that embodies those principles and asks: how can we design for play within our structures of work and study? Where and how can playful experiences be better experiences? Specifically, the book focuses on three areas where play can help: in design, in learning, and in innovation. So, this book is relevant to everyone from town planners to lecturers to product designers.

Research, Frameworks and Practical Examples

It’s bookended with an introduction and epilogue that help round out the principles (and give a great analogy of play design as a melting pot of various elements). But aside from these, the book is a collection of pieces from different authors, each focused on one perspective for play design. The common themes among them are research, frameworks, and practical examples. Most are based on solid research, well-organised. The frameworks I found most interesting: often-graphical representations of key concepts, ready to use. And the practical case studies and examples of application help bring it all to life.

The compilation nature is the thing I liked most and least about the book. The differing perspectives allow a picture to emerge that’s nuanced and complex, and there isn’t the sense that one agenda is being pushed: it’s a complex area with few points of universal agreement, and this reflects that. But the other side of this coin is that the differing authors mean there’s less coherence to this as a book than many, and when the focus for one author is less relevant or less well-written, your interest can wane.

A Taste of the Book

But that’s okay; this can be seen as a book to jump around in rather than read cover to cover, and if you focus on the chapters most relevant to you, there is some fantastic content. Some of my favourites include:

• Jesper Falke Legaard’s chapter on designing meaningful play experiences, which provides a play blueprint that really helps to pull apart, examine and improve any play design
• Jess Rahbeck’s chapter on playful tension, which unites ideas of tensions and paradoxes across theories from Piaget’s to Csikszentmihalyi’s, many of which I’d not come across, and gives some very practical scales against which to consider your own play designs
• Tilde Bekker, Ben Schouten and Landa Valk’s chapter on the lenses of play card tool, which resembles Jesse Schell’s game design lenses, but with a play rather than game design focus

Anybody who designs any kind of experience, consultation or process in which they want to enhance a sense of play and reap the rewards should find this a useful and practical guide. Some of it will almost certainly speak to you more than other parts, but as that will probably differ from reader to reader, that’s fine: a great approach with this book would be read and run with the parts that apply to your practice most.

Framing Play Design: A hands-on guide for designers, learners and Innovators is available on Amazon

The post Review of Framing Play Design first appeared on Ludogogy.

Ideas are embedded in social arrangements, which in turn produce effects.

This is, in itself, a very simple idea, but the power of the insights that can be achieved if you go along with this idea, is great indeed.

In the main the ideas that are examined in this book are the more unpleasant ones that humanity has managed to come up with. Racism, Misogyny, ideas about power which bolster Inequality. And the DS4SI put forward very convincing arguments, supported by examples of their own interventions, that we can design our way out of these societal ills.

In some ways this review is a taster for what is to come from the next issue of Ludogogy (Systems Thinking – due out in January), as this book is mostly definitely rooted in a Systems Design approach, fully acknowledging the complexity and interconnectedness of the ideas, arrangements and effects we see all around us.  With that complexity, there often comes a sense of defeat, that some problems are simply too big and too difficult for us to find solutions.

IAE provides us with a framework and a set of tools to overcome this sense of defeat, firstly by understanding the social contexts one wishes to change and then by designing the new version one truly wants, either by intervening in existing arrangements or imagining new ones.

The use of the framework and tools is amply illustrated by example of DS4SI’s own interventions such as their Public Kitchen, Lighting the Bridge (a project exploring safety and geographical division) and “Is this chair own reason why…?” (a project looking at the arrangement of the chair and how it informs power relationships, among other things, in education).

Starting to Notice

On reading this book, one starts to notice ideas, arrangements and effects everywhere, and this increased awareness brings with it a heightened sense of opportunities for design. With regular use of the tools outlined in this book, you will definitely find that the ideas start to come, regularly and rapidly.

So, what does this have to do with games or gamification. In my opinion, there are two ways in which the ideas in this book can be used when designing games ‘for good’, but just as importantly when designing games for learning or even just for fun.

Games design can embrace the ideas in this book as a new tool when designing games to tackle social issues. There are a multitude of techniques and processes which can be brought to bear. These will help to create games which reveal the hidden arrangements all around us, allowing our players to make a start in redesigning their social and physical environments, to bring about a more equitable and kind society.

As well as this direct use of the tools in the book, we can also use it as a sanity check of our work in general. Even if the game you are designing is ‘just for fun’, the principles of IAE can help you to ensure that you are not bolstering ideas and arrangements which perpetuate effects which disadvantage and discriminate.

I can recommend this little book highly to anyone involved in design of any kind, not just games design.  It is available for purchase at https://www.ds4si.org/bookshop, and please do that if you are able, because the proceeds will help DS4SI to continue their work.
It is also available via this Amazon link (which would also bring in some commission for Ludogogy)

Ideas Arrangements Effects is available on Amazon

But if the price of the book is beyond your means, DS4SI have also made it available for free in a number of locations including https://c4aa.org/2020/05/ds4si-has-a-new-book or on Scribd https://www.scribd.com/

The post Review – Ideas Arrangements Effects by DS4SI first appeared on Ludogogy.

Reality Is Broken is available on Amazon

The post Review – Reality is Broken by Jane McGonigal first appeared on Ludogogy.

This model itself grew out of an earlier model – Mechanics, Dynamics, Aesthetics (MDA). Both of these models focus on the relationship between the game designer and the player, and the game characteristics and behaviours which emerge from that relationship.

It can be seen that the MDA model relates to the Gameplay layer of the MDE model, but that the word ‘Aesthetics’ has been replaced by ‘Affect’. This was at least partly in response to the confusion caused by the use of the word ‘Aesthetics’ which many people assumed to be to do with the appearance of the game.

In reality, the word refers to the emotional response of the player to the gameplay, and is firmly in the domain of the player. The designer cannot directly design this characteristic of the game. Neither can they directly design the Dynamics of the game. The Dynamics describe the behaviours of players when they interact with the Mechanics of the game. As such, Dynamics can be influenced by, for example, a player’s past experiences, strategic choices they make during play and higher level characteristics such as preferred way of playing (e.g. Player Type).

In using this model, the designer accepts that the only aspects of the game that can be directly designed are the Mechanics. So when we talk about ‘designing a game experience’, we are really talking about creating mechanisms, rules, toys and infrastructure with which the player can interact, and using our knowledge of the probable interaction of the player with our artifacts to predict the likely experience they will have. In effect we are designing a framework, but the experience can only be created through collaboration with our silent partner, the player.

Aesthetics is a blanket term which covers a myriad of responses that may be elicited from players. Theorists have sought to describe these in greater detail. For example, Hunicke, LeBlanc and Zubek, created the following non-exhaustive list of eight in their paper, MDA: A Formal Approach to Game Design and Game Research. This list seeks to formalise what it is about a game that is ‘fun’.

1. Sensation (Game as sense-pleasure). The response to the visual and audio aspects of the game, or even taste, touch and smell if the game incorporates those.
2. Fantasy (Game as make-believe). Response to the imaginary world of the game.
3. Narrative (Game as drama). A story hook that drives the player to find out ‘what happens next’.
4. Challenge (Game as obstacle course). The satisfaction of mastery which will drive return visits until a challenge is overcome.
5. Fellowship (Game as social framework). The response to social a community aspects of the game.
6. Discovery (Game as uncharted territory). The drive to explore the game world to find what it has to offer
7. Expression (Game as self-discovery). Discovering and exercising one’s own creativity.
8. Submission (Game as pastime). Response to the game as a pleasant activity one is willing to give oneself over to.

The post Focus on… Game Design Aesthetics first appeared on Ludogogy.

I bought a copy of ‘Actionable Gamification: Beyond Points, Badges and Leaderboards’ the very day it became available. I had been a fan of Yu-kai Chou’s Octalysis framework for some time by then, and I was using what I already knew of it regularly in my learning design work. I was keen to increase my knowledge and expand my practice, as it was a model that made a lot of sense to me, I found it relatively simple to apply, and I was seeing positive results.

Actionable Gamification is available on Amazon

I felt a similar excitement and anticipation a couple of months ago when I received an email about the Behavioural Design Masterclass. The main draw for me was the promise that it would contain material not covered elsewhere, neither in the book, nor in the videos provided on the Octalysis Prime Island, gamified learning platform.

Challenging and Comprehensive

The course definitely delivered on that promise. After a (very) brief introduction to the eight core drives, we were straight into new, and quite demanding territory. Although in theory, one could attend this Masterclass with no previous experience of the Octalysis framework, I would suggest that is not the best route to getting value from this course. You really need to be hitting the ground running.

The 12 lessons split quite neatly into three broad areas, firstly, the process of using the ‘Strategy Dashboard’ to inform the design of a gamification project, secondly, the ‘Battleplan’, a more detailed plan of specific features, and thirdly, prototyping techniques, particularly wireframing. There are actually five steps, but to me, looking back at the course, these were the three which took the time.

In my mind, it was this detailed description of process that I had always felt was missing from the book, where the dashboard was alluded to but never really fully explained. Having gone through this programme, I can now see why. To give an aspiring Octalysis practitioner the detail needed would have required at least another book of the same size, and even then, I don’t think it would have hit the mark in quite the same way as this programme did.

Better than Buying a Book

To learn how to use the Dashboard and Battleplan, one needs to use it for real, and to get feedback on what is produced. A book would never have achieved this, which is why the Masterclass was the best format for the job.

Discourse Platform

The course was implemented within Discourse and structured as 12 lessons over a 30 day period, with lessons being released every other day (ish) except weekends. Each lesson built on the previous one and there were practical assignments at ‘easy’, ‘medium’ or ‘difficult’ level to carry out and share with the rest of the cohort. Discourse was an ideal platform for this process, providing a forum in which learners could share, and support each other through asking and receiving helpful comments. Viewing and commenting on five other learners’ work was one of the ‘rules’ of participating, and fully throwing oneself into this process was by far the best way of extracting the most value out of participation.

The content itself was mostly in the form of videos, created and posted in the main by Yu-kai and Chris Tomasso, and these were supported by twice weekly live Q and A calls with Yu-kai and Iain Thakrah. The quality of questions from the floor and the responses from the team were high. As the course unfolded, the success of this approach could be seen in the high quality of the work produced by the participants.

Although the content was itself informative and valuable, by far the most value was derived from the interactions between the participants and between them and the delivery team, who were highly responsive (seemingly 24 hours a day). Not everyone was able to participate at a high level (more of this later), but for those who did, this was an eye-opening and valuable (and intense) learning experience, with much cross-pollination.

Value for Money

For some, the experience may have been somewhat overwhelming. The value for money, at a price point of $1000 (which could be spread over two payments), is undeniable. Maybe it is a sad indictment of other learning programmes that people were surprised at how much they got on this course, but the pace (if you wanted to participate at ‘difficult’ level, consume all the content and fulfil a commitment to interact meaningfully with other learners) was pretty relentless.

In fairness, while the live ‘delivery’ only lasted for 30 day, there was an additional 30 days in which one could complete the programme, still with access to the forum, and the content is available to learners forever. But for the few who completed all their ‘difficult’ assignments within the first 30 days or shortly thereafter, there will have been at least a few late nights.

The Next Logical Step in Octalysis Learning

If you are serious about offering Octalysis-based gamification design to clients, or if you have a project of your own which you want to gamify, this course will amply repay the effort and cost put into it. By the end you will have a good grounding in the five stage process and some good ideas for how to proceed. You can even segue into Level 1 Octalysis Certification (and If you wish, Level 2), but be aware, you will not be able to use the same project you used for this programme for either of those.

I have a feeling that these classes will not run very often; the time overhead for those delivering it, especially Yu-kai, Chris and Iain must be considerable, and the schedule of live Q and A sessions – run as they were at different times to accommodate participants from all over the world (but still attended by the delivery team, regardless), must be exhausting. Your chances to attend may be limited (CD6 – Scarcity and Impatience). But, if you have the opportunity, and you are prepared to put in the time over the 30-60 day duration, I would recommend this highly as the ‘next step’ to becoming an accomplished Octalysis practitioner, after either reading the book and/or accessing Octalysis Prime.

Actionable Gamification is available on Amazon

The post Review – Yu-kai Chou’s Behavioural Design Masterclass first appeared on Ludogogy.

However, there is another agreement that we have to make when playing a game. That is the lusory agreement and the adoption of the lusory attitude in game play. But what is this lusory attitude? What does it include and how we encourage it as designers and maintain it as a fellow player?

This article will review the lusory attitude of games. It includes a review of play in games as well as an overview of the “lusory agreement.” Part of this agreement includes players adhering to the rules of the game. While rules are important formal structures of games they aren’t the only thing that is involved in the lusory agreement. Players’ attitudes and mindsets also impact their agreement. This agreement should prevent and discourage players from acting in “bad faith” when making decisions in games.  The article closes on the social contract and social agreement of games as part of the lusory attitude.

Play

Play composes the basic level of activity in games. That’s because play represents players’ intrinsic motivations to engage with the game, each other, and the environment.

Play is involved in all games. Play in general is something of a socio-cultural manifestation for what we want, experience, and achieve while playing games. When we play we engage without direction. But when playing games we often have a clear goal, outcome, or achievement that we aim for.

Both play and games require that we enter a specific and special place called the “magic circle” that requires use to suspend our disbelief. We want to become an entity that is inside the game as well as someone who is experiencing it in real time. Playing means that we don’t always have to come away with something physical and tangible. Most of us don’t play games for money. We play games because we enjoy them. We don’t play for some sort of external reward.

Perhaps the biggest takeaway that we get from games is that we become engrossed in them. This represents a perfect harmony between player and the game where we’re engaging at the top of our abilities. This is called the “flow state” and is exists right between being bored and frustrated in games.  In the flow state we are challenged to achieve more than we thought we could.

This flow state represents something that is part of play that isn’t always linked to a biological need to play games. Nor is it something that we feel compelled to routinely seek out and experience. But when we’re in the flow state we feel entranced. We want to keep playing the game. We don’t’ want to leave.

However, sometimes that “trance” of the flow state is broken when we lose, fail, or otherwise upset the balance in the game. These failures from players come about when we are defeated by our adversaries; when we run out of time; resources; or sometimes even patience. But these failures are often part of what makes the game engaging. We accept these failures as consequences for our continued desire to continue playing the game.

So we have to make a decision to continue playing. But we have to play by the game’s rules. Those rules state that we have to achieve, accomplish, or satisfy the objective of the game using the means provided to us. Often those are “inefficient means.” Why should I have to hit the baseball in order to run around the diamond? Can’t I just tap home plate once and score a run?

Of course any player could do this. But that wouldn’t follow any of the rules of the game. Would that even be fun? Pursing these “inefficient means” of accomplishing the game goals is the next choice that players make in the “magic circle” of games. This includes our tacit approval of the “lusory agreement.”

“The Lusory Agreement”

The lusory attitude of players is informed and shaped by their lusory agreement in the game. That lusory agreement is based on players’ decision to play the game by its established and socialized set of rules. This is based on the Latin word “ludus” meaning game.  The agreement comes from players understanding (and acknowledgement) that they will play the game according to its rules and to the best of their abilities.

The lusory agreement begins with players acknowledging that they will play the game according to its established rule set. It further acknowledges that players accept these rules as the inefficient means of achieving the game’s objectives. For example in golf the objective of the game is to drive the ball from the tee into the hole. Players agree to drive using a set of clubs. They do this instead of throwing the ball or walking directly to the hole and placing it there by hand. Golfers acknowledge that they will pursue the objective of the game by following these rules.

However, those are the established rules for the game that players must abide by. But everything else is up to the players. They are free to play the game – and thus – create meaningful opportunities to make decisions that affect their status and outcome of the game. Players can develop their own tactics and strategies. If you’re like me you can begin trash talking the other mini-golf players in your group (it’s part of the game – trust me).

Frustration is inevitable when it comes to playing really challenging games – especially if you’re playing against very skilled opponents.  But the lusory agreement of the game and its accompanying magic circle; make is so that the actions contained within the game and the results of those actions are limited. Those consequences are constrained to the game and aren’t supposed to leave it. Just like the results of playing within the magic circle.

Video games take the lusory attitude one step further by codifying players’ adherence to the rules through a series of automations. Players of course can cheat with enough know-how; gumption; and drive. But doing so violates the lusory attitude of the game.

That means that even with the lusory attitude on players’ agreements there remains a wide void between players’ meaningful choices and what they can (and will do) within the game. Player behavior is a complex concept. It’s made up of choices; constraints; and their own driving factors influenced by their player type.  However, all player behaviors begin with the first choice: choosing to play the game by the game’s rules.

Those rules form the first formal structure of games. The rules are the construct and the structure for how players adhere to the lusory agreement in order to achieve the game’s end goals and objectives.

Rules

The rules are the formal constraint of games. They are the aspect that often make the game challenging, non-trivial, and require some degree of effort or thinking in order to achieve the game’s objectives. The lusory attitude that players adopt acknowledges that players abide by these rules.

However these rules aren’t always clear between what is expected  of the designer and what is expected to play the game from the other players. That means that rules can be broken down into two separate categories. Explicit rules are part of the formal elements of the game. The implicit rules are part of the social contract and the lusory attitude of game that players adhere to when playing.

Often there is a gray area that emerges from both the explicit and implicit rules of games. That’s when judgments need to be made by other players on edge cases or other interpretations between the explicit rules and players’ choices.  Often these are handled by impartial third parties. We see these in sports with referees, umpires, and other officials who mitigate these rules interpretations and apply rulings that are supposed to support the integrity of the game.

However, in other arenas like in table top games, the inclusion of an impartial third party isn’t always an option. That means that players themselves need to police their own behavior and the behaviors of their fellow players. This often gives birth to “house rules” or other forms of implicit social agreements that players adopt that arise from these cases.

These house rules aren’t necessarily a bad thing. In reality they provide additional cultural flavor and influence that players have over a game. The combination of which affects one of the most influential areas of the lusory attitude: the mindset of each player.

Attitude & Mindset

The lusory attitude is one of the first decisions that players make when deciding to play the game. As such their altitude at the time of the agreement is what influences and flavors their play.

However, this decision doesn’t exist in a vacuum and isn’t binary. A player can’t decide to adhere to the rules of the game and immediately have fun. Instead, players also bring a playful attitude with them when they agree to play. That in turn affects the decision of other players and ultimately the player experience from which everyone benefits.

There are many ways to exhibit and demonstrate this playful attitude. One of the best ways is understanding that the game’s rules form an artificial (but necessary) boundary between efficiency and challenge when accomplishing the game’s objectives. This “voluntary attempt to overcome unnecessary obstacles” by Bernard Suits greatly influences this playful attitude of players in the game.

This playful attitude is also what contextualizes players’ decisions within the game. Without the lusory attitude, players decisions become objective actions without any motivation or connection. Games aren’t just about the actions that individual players take. Game dynamics come from those decisions by players, with players, and inside the game.

These game dynamics inform and affect the game play for other players. Often this comes when all players “take the game seriously.” That doesn’t mean that they have to play competitively or that they play aggressively. Rather, they look at the game as a serious commitment to accomplishing the objectives of the game within its constraints.

Because of this it’s important that games encourage, engage, and embolden players to want to “win” at the game. But the importance ultimately is not that players win. It’s that they adhere to the common goal of winning. Through their lusory attitude they determine that the serious goal of winning is part of their agreement and desire to play.

Bad Faith

The lusory agreement in games is the first really meaningful decisions that players make when they decide to play the game. The lusory attitude on the other hand is much more transient and can shift and change according to the player’s behavior, feelings, and connection to other players and the game.

The lusory attitude is then subject to “bad faith” move by players. Some of these can be more objective than others. That’s when players want to maximize “efficiency” of actions in their attempt to adhere to the rules, but not necessarily the spirit, of the game.

Otherwise, players can take on a more subjective approach. This can include taking “sub-optimal” actions that would put them in a worse or non-optimal position than their opponents. Sometimes this could be done out of frustration: if players don’t feel that they have the ability or agency to affect or influence the game in their favor.

Sometimes these can be done out of spite. Players don’t feel that their actions can help them. However, they can still act to negatively affect other players. This can happen in table top games when “king-making” becomes an action. A player may not be able to win; but they can influence who of the remaining players can win.

This bad faith convention in the lusory attitude affects all who play the game. This can come from more tangible outcomes such as having the game end early, prematurely, or before a really satisfying resolution. Otherwise, players could take advantage of loopholes within the game or house rules of the game to exploit an advantage that would compromise the lusory agreement.

At face value these “bad faith” decisions are at the heart trust issues. The lusory attitude is based on players trusting one another to pursue the goals of the game within its defined boundaries. If all players cannot adhere to that then the game’s integrity is at stake. And why place the integrity at stake if we cannot even enjoy the process of succeeding through “inefficient means?”

At the most extreme end of the spectrum these “bad faith” decisions result in cheating. Players completely, purposefully, and willfully subvert the rules of the game for their own benefit. Most gamers cannot stand cheaters because of their violation of the integrity of the game. However, all gamers shouldn’t tolerate cheaters because they haven’t even said yes to the most basic decision of the game: the option to play fairly with others.

Social Agreement & Social Contract

At its heart the lusory attitude and agreement is a social contract. It’s an agreement made between the players and the game. Its’ a decision to follow the rules and put one’s best effort forward into winning by accomplishing the objectives of the game. This could be through competition against one another or cooperation in order to achieve a common goal.

The lusory attitude is contentious for players because this is often a social construct of games. There are no rules books which state that players MUST abide by their decision to play and engage with one another. That is already understood when they picked up the controller, the board game, or their tablet.

This doesn’t mean that every game, match, or interaction of the activity will be enjoyable. But we commit ourselves to experiencing this, and a range of other emotions, after we’ve decided to play.

However, after we’ve made the decision to play we have to continuously ask ourselves if we want to continue to play. We are often provided ways for us to continually “opt-in” to the game. Each time we agree to continue playing we objectively and socially dedicate ourselves to the pursuit of the lusory attitude.

We have to make that decision every time we want to cross into the magic circle of games. We make that decision in order to distinguish and separate ourselves from what we are here in our own reality and what we could become in the game. Each game has its own set of rules and expectations. By agreeing to play we become ambassadors from the real world to the game world.

By agreeing to play we create personal and social meaning between us, the game, and our fellow players.

Takeaways

This article reviewed the lusory attitude and agreement in games. It included an overview of play in games as well as how play informs the “lusory agreement.” Game rules as well as player behaviors and attitudes were discussed. Specifically how they inform players’ agreement to play the game according to established rules.  Player mindset also affects the lusory agreement. This can most negatively affect players making “bad faith” decisions in games. The article closed on the social contract and social agreement of games and how players’ choices affect their lusory attitude.

This article was originally published by Dave in his blog What is the Lusory Attitude?

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Game theory originated in the study of zero-sum games. In these games, the gains or losses of each participant are balanced by the gains or losses of the other participants. More recently, game theory has been used to describe and explain a much wider range of interaction behaviours. The term is now used to refer generally to the scientific study of logical decision making in humans, animals, and computers.

Toy games – matching pennies

The toy games which are of particular interest when looking at sustainability and environmental issues are:

• The Prisoner’s Dilemma
• Security Dilemma
• The Tragedy of the Commons

The assumption is made in these games that all players will act as rational decision-makers, that is, that they will act to maximise their own return.

In simple toy games of pure conflict, we can pitch one rational actor against another. ‘Matching Pennies’ is one such game.

‘Even’ and ‘Odd’ are matching pennies. Each secretly turns a penny in their pocket, and they reveal them simultaneously.  ‘Even’ wins if the pennies match; ‘Odd’ wins if they don’t. This is a zero-sum game in that one person’s loss exactly equates to the other’s gain.

Even’s strategy

Odd’s strategy

The idea of a ‘strategy’ in this case is somewhat redundant. Since each player has an equal probability of choosing heads or tails and does so at random, neither Odd nor Even has any reason to play Heads (or Tails), as a ‘best response’ to their opponent’s move. Another way of stating this is to say that there is no pure strategy Nash Equilibrium in this situation.

Nash Equilibrium

A Nash Equilibrium occurs where no player has an incentive to deviate from his chosen strategy after considering an opponent’s choice. In other words, there is a fixed ‘best response’ to the game for each player. The Nash Equilibrium is the result which emerges from both players playing their ‘best response’.

Minimax and Maximin

Rational actors will seek to maximise their own minimum gain or minimise their maximum loss (or minimise the maximum gains of the other players). These are the Maximin and Minimax strategies put forward by Von Neumann. The Nash Equilibrium occurs if these rational choices lead to a best response from each player. This best response is known as a ‘dominant strategy’.

See the ‘mixed outcome’ game below. It is a mixed outcome game because, unlike a zero-sum game, where the losses of one player equal the gains of another, the gains of one player can be different to the losses of the other.

N.B. in the payoff table below the first number in each pair is Alice’s (row player) payoff, the second is Bob’s (column player).

Alice has three choices she can make (a, b, or c). Her Maximin value is the highest value she can be sure to get without knowing what Bob will play. In this payoff table that is 2, by playing ‘a’. If she plays either ‘b’ or ‘c’, she risks scoring a negative value.

If she plays a Maximin strategy she will choose ‘a’ as her play.

Her Minimax value is the minimum value that Bob can force her to achieve, in the case that Bob does not know what she will do. In this payoff table, her minimax value is 4 (if Bob plays ‘X’, she can get 5, if ‘Y’, 4).

Bob’s Maximin strategy is to play ‘X’, which means he can achieve a minimum of 0. Playing ‘Y’ would put him at risk of getting -35. Bob’s minimax value is 1. If Alice plays ‘a’ that is the minimum he can achieve, if ‘b’, 2, and if ‘c’, also 1.

If both players play their Maximin strategy the payoff will be (3,1)

Another way of explaining Minimax value is to say that it is the largest value the player can be sure to get when they know the actions of the other players. For example, Alice would only play ‘b’ to achieve her Minimax value of 4, if she knew that Bob had played Y, because she risks getting -60 by playing ‘b’ without that knowledge.

If the players are playing without knowledge, to minimise the maximum value for their opponents, Alice’s Minimax strategy would be to play either ‘a’ or ‘c’ (both have a minimax value of 1 for Bob).

Bob’s Minimax strategy would be to play ‘Y’ (for a minimax of 4 for Alice)
The payoff for Y,a is (2,-35) and for Y,c, (-15,1)

So without prior knowledge, in this mixed outcome game, each player is best playing their Maximin strategy.

The Nash Equilibrium in a zero-sum game

In the case of a zero sum game, the Nash Equilibrium is the same as the Minimax.

In playing this game Alice might reason thus:

“With ‘b’, I could lose 2 points but can win only 1, and with ‘a’ I can lose 0 but can win 4, so ‘a’ looks a lot better.”

Bob would reason in a similar way

“With ‘X’, I could lose up to 4 points, and with ‘Y’ I can lose 0 but can win 2, so ‘Y’ looks a lot better.”

The Nash Equilibrium is circled above. Alice has no incentive to change her decisions, even if she knows what Bob has chosen. If Bob chooses X, it is still best for Alice to choose ‘a’ because 4>0. If he chooses Y, it is still best for her to choose ‘a’ because 0 > -4.

Bob has no incentive to change either. If Alice choose ‘a’, it is best for Bob to choose ‘Y’ because 0> -4, and if she chooses ‘b’, it is best for him to choose ‘Y’ because 2>-1.

And we can also see that the Nash Equilibrium is the same as the Minimax solution. Alice will play ‘a’ to restrict Bob to maximum gain of 0 and Bob will play ‘Y’ to restrict Alice to a maximum gain of 0 also.

This could also be described in terms of the Nash Equilibrium (or minimax solution) being the ‘best of the worst case scenarios’. Clearly both of the players could have scored better, but their ‘best response’ results in them minimising their losses not maximising their gains.

Any game of pure conflict can be modelled as a zero-sum game – the win of one party can exactly equal the losses of the other – as we can see in the payout matrix above.

How do we decide on the payoff values?

When dealing with conflict and cooperation – games with mixed outcomes, we need a better way of describing player motivation.  Economists invented the idea of utility. This allows us to express the outcomes of a game with a numeric value.  Imagine that it works as a kind of utility scale – like the scale on a thermometer – a ‘util’.

This also answers the question, which might have been on your mind up until now, ‘Where do the values in the payout matrices come from?’ (regardless of whether are looking at zero-sum or mixed outcomes).

How do we assign a util value to a particular outcome? The number of utils that any outcome is worth equals the size of the risk someone is willing to take to attain it.  How many utils will Alice assign to passing a particular exam?

1. First decide your scale, e.g. 0 to 100 where 0 is assigned to the worst outcome Alice might encounter and 100 to the best.
2. Next offer Alice a series of (free) lottery tickets where the only possible prizes are either the best or worst outcome and ask her if she would swap it for passing her exam.
3. Each successive ticket has a better percentage chance of achieving the best outcome than the preceding one
4. If the ticket which makes her say ‘yes’ has a 75% chance of her winning the best outcome, we say that passing the exam is worth 75 utils to her.

Battle of the Sexes

To demonstrate, consider the following game of mixed motivation ‘Battle of the Sexes’.  Alice and Bob are arguing over what to do on Saturday afternoon. Alice wants to go to a Star Trek convention. Bob wants to go the Ballet. They are still arguing and have not made a decision when they get accidentally separated. They now have to independently make their way to the Ballet or the Star Trek Convention, with no knowledge of what the other will do. For both of them, the best outcome is that they get to do their preferred activity, AND be in the company of the other person, but even if they have to do their least preferred activity, they attach some utility to being with the other person. There is no utility attached to being alone- even in the case that they are doing their preferred activity. Awwww – sweet, ain’t it?

There are two pure strategy Nash Equilibria here, which are circled.  Alice’s best strategy is on the left and Bob’s on the right. There are two justifications for why Nash Equilibria will always emerge from games with payoffs like these

Rational explanation – Suppose a book existed with a list of all games and an authoritative recommendation on which how each game should be played.  Each solution would have to be a Nash Equilibrium or it would be rational for at least one player to deviate from the advice and it would no longer be authoritative.

Evolutionary – Processes that favour fitter strategies against less successful ones, can only stop when a Nash Equilibrium is reached, because only then will all the strategies be as fit as they can be.

Let us now look at some ‘toy games’ with particular relevance to sustainability. Firstly, we will look at probably the most famous ‘toy game’ – The Prisoner’s Dilemma

The Prisoner’s Dilemma

This game explores why rational actors may not cooperate with each other, even when it is in their best interest to do so.

Two alleged criminals – members of the same gang – are arrested and taken in for questioning. Each prisoner is in solitary confinement and cannot communicate with the other. The police do not have enough evidence to charge either with the more serious offence which they believe they have committed, but they have enough to convict both on a lesser charge. Simultaneously, the police offer each prisoner a bargain. Each prisoner is given the opportunity either to betray his gang-mate by testifying that the other committed the crime, or to cooperate with the other by remaining silent. The possible outcomes are:

• If A and B each betray the other, each of them serves two years in prison
• If A betrays B but B remains silent, A will be set free and B will serve three years in prison (and vice versa)
• If A and B both remain silent, both of them will serve only one year in prison (on the lesser charge).

Although both players would clearly do best by co-operating, the rational choice for each is to betray, because the risk of co-operating is too great in the case that the other betrays.  As a result, the Nash Equilibrium (circled) ensures that each prisoner receives a sentence of 2 years – worse than the outcome if they had cooperated.

The story of the Prisoner’s Dilemma is, of course, incidental – what makes the PD into the PD is the payoff table associated with it.  The Nash Equilibrium will always emerge because the payoffs will make it happen.  If you don’t end up at an NE then you aren’t playing the PD.

In the game, there are a number of assumptions which have to hold in order for it to play out as it does.  The players are ‘rational actors’. Prisoners have no way of rewarding or punishing each other, other than the prison sentences. Furthermore, their future reputation is unaffected by the single decision they make. Under these assumptions, betraying a partner offers a greater reward than cooperating with them, and therefore rational actors will always ‘betray’.

In reality, things are much less bleak. Humans do not always act as ‘rational actors’ and display a systemic bias towards co-operative behaviour.

Security Dilemma

A related game is ‘Security Dilemma’, which has been used to demonstrate aspects of the arms race /disarmament. In this case, the payoff are based on two criteria, cost and security. There is a financial cost in maintaining a nuclear deterrent, but if you have a deterrent and your ‘enemy’ does not, your country is more secure.

The payoff table reflects this by showing that the outcome where both countries choose to be ‘Hawks’ – to maintain a deterrent, they neither do as well as if they had both decided to disarm (Dove).  Both of these decision pairs (Dove, Dove) and (Hawk, Hawk) give equal payouts, as both countries are now equally ‘secure’, but (H, H) is a less good option, because both countries are incurring major expense.

The worst outcome for each country is that they opt to be Doves while the other player opts to be a Hawk.  The Nash Equilibrium for this game is therefore the (H, H) decision with a (2, 2) payout.  But countries do unilaterally disarm, so again, although these kinds of games are useful, they are too simplistic to represent reality in complex situations.

The Tragedy of the Commons

The Tragedy of the Commons is a game with high relevance to the challenges of environmental sustainability.  It is also a game, which plays out with great fidelity in the ‘real world’, in the way that humans choose to exploit (or conserve) ‘common goods’ such as land, freshwater or the oceans.

A commonly given example is of a piece of common land on which a number of farmers are allowed to graze their sheep. The land is capable of supporting 20 sheep, and each of 10 farmers take two of their sheep to the common daily to graze.

All is well. The common is able to support this level of use, and the grass grows back at an appropriate and sustainable rate.

However, if each farmer behaves as a rational actor, it is in his interests to overexploit the common. The utility he will gain by bringing an extra sheep to the common will far outweigh any negative effects on him. As he alone profits from the value of the additional sheep, in wool or meat, the utility will be very near to +1. That this will just a short-term gain is largely immaterial unless some kind of conservation intervention is made which prioritises the utility for the many over the utility for each individual.

Without such intervention the common will be overused and become less useful to everyone, or even be totally destroyed.

This can be modelled as a toy game with a payoff matrix as above, but this can only work in quite simple cases.  For example, we can create a matrix where only two farmers are using the common, and show the relative utility depending on how many animals each brings to the common.  This in effect is like ‘playing’ the tragedy of the Commons as if it were The Prisoner’s Dilemma. Such a matrix might look like this. This is a much smaller common than the one mentioned above, where it is best to only graze two sheep.

It would be optimal (collectively) in this case, for each farmer to graze only one sheep, but individually it is best for each to bring two sheep, thus creating a Nash Equilibrium where each ends up with a less well-fed sheep

Modelling the Tragedy of the Commons as the Prisoner’s Dilemma is not without its problems. This is because this is not actually a problem which can be described in terms of a dominant strategy.  This is because the strategy of each beneficiary of a common is reliant on what the others do.  If you remember from the above, a dominant strategy is dominant only because it is independent of the decisions of other players.

However, more complex mathematical models of problems such as the Tragedy of the Commons are beyond the scope of this brief overview of toy games in game theory, and the Prisoner’s Dilemma approximation of the Tragedy of the Commons does provide a useful first look at the underlying principles of the problem.

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