 The responsive controls and precisely crafted levels of Mario, the booming weaponry and sense of empowerment in Doom, and the intricate systemic elements at play in SimCity, all might seem very different, but they are united under a commonly understood purpose for games, fun. In this seminal book, A Theory of Fun, Raph Koster argues that the fun of a game comes from its ability to provide us a rich possibility space for learning, a space that grabs our attention, challenges us, and reveals infinite depth. For example, Tic Tac Toe, as a simple game with a dominant solution, is less fun than Go, a game with as many permutations as there are stars in the universe. Its denser possibility space means we have much more to learn and engage with. Koster asserts that we are a pattern recognition species who thinks in cognitive chunks, which means we can store an incredible array of patterns in our head to bring to bear in games. As he states, games are concentrated chunks ready for our brains to chew on and are fundamentally about abstraction. Human is just the dopamine in our brains, firing when it is presented with a new situation to learn from. What do games teach us, though? Chess teaches us strategy and foresight, civilization teaches us systemic analysis and resource management, and a game like poker teaches us deception and reading people's lies. These are what he calls type 1 games, games that are about thinking. Type 2 games are more about reflex-based skills, so think of the precise inputs required in Mario, the combo memorization and execution in Street Fighter, and the sharp reflexes you need in any shooter. He states, Fun is the feedback the brain gives us when we are absorbing patterns for learning purposes. He concludes by claiming that an understanding of fun is integral to our understanding of games as an art form, and that games are fundamentally a creative art that gives us the ability to learn. Fun is about learning, then, about learning new skills, strategies, and concepts in a confined domain that test us on a variety of cognitive and dexterous skills. It seems so simple, but this is hardly the only conceptualization of fun we have had in our medium. Ever since a bug in the code of space invaders sent aliens careening faster towards us as we killed them, we discovered the joy of difficulty escalation, and this is now standard in every kind of game. This maps onto a now commonly understood phenomena, flow theory, which argues that a sense of engagement comes from having a challenge that rises in proportion to our abilities. From Mario to Tetris to Doom, difficulty is ramped up over a game on both qualitative and quantitative grounds to keep us learning new things to provide a space for us to grok continuously. A host of conditions need to be met for this, including having perceivable feedback for our actions, clear goals and control over our abilities. Games that have exceptional control allow us to feel fully agentic and then challenge over time puts us in this elusive flow state, where time itself washes away. Two other books, Steve Swink's Game Feel and Michael Sellers' Advanced Game Design allow us to better understand the differences between Type 1 and 2 fun. In Game Feel, Swink argues that reflex-based games need direct control, polishing effects and a mechanical context. For example, Doom not only has fluid controls, but sound effects and music to amplify the frenzy and level design that incentivizes push-forward combat. Let's also not forget the importance of power-ups and scoring systems, pioneered in Pac-Man and early arcade games, which creates a context that encourages the most fun type of play. Combining these elements lets us examine why games are as engaging as they are. Devil May Cry 3 has a variety of versatile inputs that allow thrusts, launches, combos and weapon switching, but also has a style meter that encourages creativity, while SSX has a boost system that encourages risky play, all while layering in dynamic music to highlight the impact of your inputs. In Michael Sellers' work, we get a better sense of how Type 1 fun is crafted, by creating systems and longer engagement loops. Games like Civilization and SimCity present resource optimization puzzles, as you figure out how to build cities and conquer empires. These are based on systemic devices called engines, economies, and ecologies, which are mechanisms to understand how resources interact with each other. Games of this ilk enable long-term strategic decision making, extremely deep and dense possibility spaces for learning, and allow for intentionality, for planning with intent to affect change in a system. In chess, much of the fun comes from plotting your moves between turns, as you try to anticipate the state space as it evolves. So we seem to have a pretty robust understanding of what fun is, and also how to apply it in game design, but this does not mean there are not problems with this pursuit in game formalism. One criticism is that this idea of fun does not account for different aesthetics of play and different player preferences. Surely all games are not about as something as reductive as fun. What about the intense pacing of Uncharted, but the narrative structure it presents looks much like Flow Theory? What about the meaningful mechanics of Eco, but it uses systems we need to learn to communicate its core rhetoric of empathy and love? However, isn't the word fun becoming reductive at this point? To broaden our understanding of fun, Nicole Lozaro presented her four keys of fun framework, which identifies different types of fun for different players. There is hard fun, which covers most of what we have been examining this video, but there is also people fun, easy fun and serious fun. People fun comes from the joy of interacting with others, as we do in any number of cooperative games. Easy fun is about novelty and curiosity, where there would be when we explore new lands or walk through beautifully rendered environments. This broader understanding of fun does not need to conflict with the idea of learning. We learn to be with each other when we cooperate. We learn about themes, ideas and emotions as we explore the house and gone home. We learn about new ideas and concepts as we interface with the complexities of the witness. Learning is happening no matter what type of fun is being invoked. It is built into all forms of play and storytelling. The word fun is still reductive though. It seems to conflict with serious inquiry, with art, with a higher purpose. And there are a whole host of aesthetics of play, emotions and ideas that make no sense in light of our understanding of fun. However, this does not mean that there is anything wrong with pursuing fun as a design goal. Games can be about fun, it's a beautiful pursuit, but they can also be about anything they want. We shouldn't expect all games to be fun, but we shouldn't reject games because that's all they are as well. Regardless, with all these caveats in mind, we still have a lot of work to do when it comes to our understanding of fun. We have a sense it is about learning, feedback, feel and flow, but we need to be precise in how we articulate this and propose tools that allow us to measure it, replicate it and if need be, subvert it. This is why we need a theory of fun.