Nowadays, when most people hear the term ‘Cybernetics’ they will tend to associate it with computer technology, possibly in a sci-fi or futuristic context. However, the term existed well before the age of digital computing. In 1948, mathematician Norbert Weiner wrote a book, ‘Cybernetics or Control and Communication in the Animal and the Machine’, where the term, taken from the Greek for ‘(boat) pilot’, first appeared (in the modern era, at any rate). Over the years, the field of cybernetics was advanced by practitioners such as Stafford Beer, who was the first to try to apply it to business (and indeed government) organisations, creating the sub-field of Management Cybernetics. Today the term is rarely used in this original form, with the disciplines it once covered more likely to be referred to as ‘Control Theory’ or ‘Information Theory’.
The field is a rich one, encompassing formal structures of systems, how they dynamically change over time, how system elements interact and many other aspects. For the purposes of this article, I will focus on a relatively narrow aspect of games as cybernetic systems – Feedback Loops.
In their simplest form, cybernetic systems consist of three components. A sensor, takes in information (feedback) from the environment, and provides it to the controller. The controller uses this information to decide whether the system is deviating from an established norm, and provides instruction to the actuator which produces some form of output which affects the environment. In many Systems Thinking textbooks, the first example of this that a learner will be presented with is a heating thermostat, where the sensor detects the temperature in a room, the controller compares that to the ideal temperature set by the user, and then instructs an actuator to switch the heating on or off (or issues no instruction if tno action is required).
The thermostat example shows a negative feedback loop – not because its effects are unwanted, but because it causes a situation of equilibrium, maintaining the status quo. Positive feedback loops on the other hand create a cumulative change. These can obviously go in one of two directions; producing more of something (rising temperature, economic growth, increasing infection rates) or less, ultimately moving towards zero or a standstill (population decline, economic recession, absolute zero). The heating thermostat could be set to operate as a positive feedback loop if was designed to activate if the sensor detected that the temperature was greater than a certain minimum – resulting in an ever-rising temperature.
So, two questions present themselves with respect to (learning) games design. First, how might we use these concepts to inform games design? Second, how might we create games which can be used for learning around the concepts of complex systems?
One game which definitely displays a positive feedback loop, and is, as a result, one of my least favourites, and my go-to example of a crappy game experience, is ‘Monopoly’. Once a player has money, or property, there is a tendency for them to gain more. It is extremely difficult, if not impossible, without a great deal of luck (which a well-designed game experience should never rely on too heavily) for a fiscally-challenged player to eventually triumph. While this is probably a very accurate representation of the way that deregulated capitalism actually works, as a ‘fun’ experience, it sucks – especially given that players may be playing as escapism (possibly precisely because of the adverse effects of deregulated capitalism).
It is useful for a games designer to use the lens of Cybernetic Systems when deciding on the rules of their games because the rules constitute the sensors, controllers and actuators in your game, and will help to create the play experience in terms of its ‘flow’. Will your game tend towards a steady state, or will the experience wildly oscillate? Do you risk positive feedback loops that lead to unbalanced experiences (as in Monopoly), or the tendency for the game to reach unplayable ‘stalemate’ situations? How do feedback loops maintain competition (or cooperation)?
At any point in a game, there is a current game state – represented by, for example, the positions of pieces on a board, the current score or other stats of players or the location in which play is currently set – or any other similar ‘snapshot’ information. To some extent, this is ‘outside’ of the system, in the same way that the temperature of the room is external to the thermostat because it is neither sensor, nor controller, nor actuator (although the current information contained in those, or the impact of them, may be represented)
The scoring system is the ‘sensor’ of the game in that it is a measure of how the player is performing.
In most games, the player would be able to use the scoring mechanism to see the impact of previous decisions they have made in the game, and to hypothesise what might be the effect on the score of the next decisions they are planning. Even in games which don’t ‘keep score’ in a recognisably numeric way, there are ways of a player discerning how well they are doing and linking that performance with their past and future decisions. In Chess, for example, you could see the effect of your moves in the relative material advantage of yourself and your opponent, whether pieces are safe or threatened, and so on.
The controller in this situation is the player (usually a human), who receives the information from the scoring system, and uses that, along with their knowledge of the game system, skill in play etc. to make a decision about what to do next. They can then set in motion a game event or set of events – the actuator (casting this spell, moving that piece, or even declining to play at all, dependent on the actions that the game structure, rules and components, makes available to them).
The above is adapted from a formalised model which can assist you in games design, created by Marc LeBlanc. His way of modelling games as feedback systems provides us with useful tools when we are creating our own rulesets. See his collected ‘rants’ for a much more detailed description of the above, and guidance on using positive and negative feedback loops, illustrated through two games – ‘Negative Feedback Basketball’, and you’ve guessed it ‘Positive Feedback Basketball’. He is also the originator of the MDA design model, which is the subject of a previous article in this magazine.
As a counter-example to Monopoly, and to show that positive feedback loops are not necessarily always bad games design. I am happy to report that while recently playing ‘Guitar Hero’ (‘Heartbreaker’, by Pat Benatar, if you are interested), I managed to successfully complete a sequence of star-shaped notes, thus activating star power and therefore narrowly saving myself from being booed off stage.*
A currently popular game mechanic (which I, personally, am obsessed with) is ‘engine-building’ (or tableau-building), which is used in some really great games – ‘Wingspan’, being the most famous, but honourable mentions have to go to ‘Everdell’ and ‘Castle Dice’. This mechanic is an elegant implementation of positive feedback loops to build almost endless permutations of advantageous growth scenarios.
So how might we create games for learning around these concepts? Search of the available literature reveals that many researchers have posited that lots of off-the-shelf games contain excellent raw material for learning about complex systems. For example, Dana Nicula and Sorina Constantinescu of Bucharest University wrote a paper about using Catan as a learning tool. https://www.utgjiu.ro/revista/ec/pdf/2017-02.Volumul_2_Special/27_Nicula.pdf
My particular favourite cybernetics game dates from a time closer to the birth of cybernetics as a discipline (as you can probably tell by the width of the collar on the box). Trippples was published in 1973, by an actual psycho-cybernetics researcher, William T Powers. According to the rulebook,
‘Trippples requires that its players consider each move from the “feedback” game theory point of view:
Each move is not only an advance of the player’s piece, but puts definite limitations on the “move options” of the opposing player – and vice versa’
The playing pieces are 64 wooden tiles of three kinds
- Depicting either a circle or square (starting and end pieces of two players/teams (four tiles)
- Blank tiles showing ‘no-go’ areas (four tiles)
- Showing all the possible combinations of sets of three directional arrows (56 tiles)
The tiles are laid before play to create a playing surface upon which the players will make their moves with transparent markers. The aim of the player is to win by being the first to reach the ‘end’ tile (e.g. an unfilled circle tile), which is positioned in the diagonally opposite corner from their ‘start’ tile (e.g. a filled circle tile). They do this by moving their marker by one tile at a time either vertically, horizontally, or diagonally, while avoiding the four central blank tiles.
So far, so simple, but where the game models the feedback systems of complex adaptive systems is in its central rule. The moves that a player can make are constrained by the directional arrows underneath their opponent’s marker. In the words of the rulebook
‘Trippples is played in the arena of psycho-cybernetics, where the mind is continuously challenged to process rapidly changing information and formulate new strategies as each move is made and new options are opened.’
in other words, when your opponent makes a move, you will be presented with three options for the way in which you can move (or fewer if constrained by moves which would take you over the surface edge or into the ‘no-go’ blank tiles). You must then try to find the move which best meets the requirements of:
- Moving you closer to your own win-state
- Restricting the next move of your opponent so that he does not gain an advantage
- Forcing your opponent’s next move to provide you with advantageous options for your next move
- …and so on, to as many levels of recursion you can manage to hold in your head
Think back to the thermostat, and the concepts of positive and negative feedback loops. What we have here are two feedback loops (imagine a heating system trying to raise the temperature to x, operating in the same room with a cooling system trying to achieve a much cooler y). A tug of war ensues, which is where the competition in the game comes from.
The rules above represent just one of the suggested ways of playing Trippples given in the rulebook, and other versions are suggested. There is even a plea in the rulebook for serious players to write to the inventors (postal address given – this was the 70s) with their ideas for the as yet ‘undiscovered’ versions of the game. In some senses, Trippples was born into the wrong time (and this makes me a little bit sad). If it had been created in the age of the Internet, there might well be thriving communities of players/creators making new games for this Games System (see the ‘Focus on…’ article on other games system, also in this issue), as there are for systems like Looney Pyramids. Maybe Ludogogy readers could start a Trippples revival!!
Looking at games design, and its potential application, through the lens of cybernetic systems, emphasises the suitability of games for creating learning experiences about and within complex systems. In this age of complex systemic issues; ecosystem degradation, systemic racism, climate crises, the spread of mis- (and dis-)information, pandemics and so on, the opportunities are greater than ever for creating playful experiences that are not only ‘fun’ but which help us to make better futures.
Sarah Le-Fevre is a learning professional who specialises in games-based learning and systems practice for learning design. She is also a Lego® Serious Play® facilitator. A real board games nerd, she is considering having her floors reinforced to support the ever increasing weight of the boxes. Sarah lives in Oxfordshire with her husband, younger daughter, a beautiful Bengal cat and two rats. Sarah is the editor of Ludogogy Magazine. Contact her at firstname.lastname@example.org