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At its core, the process of creating an educational game is ultimately one of crafting a software product that will engender a particular experience for the player – an experience that will cause the player to acquire the skills or knowledge being taught. There are many factors that contribute to such an experience, such as the subject-matter content, the graphics, the audio, the gameplay mechanics, the dialog… but one of the most important – and one of the most often overlooked – is the game’s AI. It is the AI which creates the behavior of both the characters in the game and of the game as a whole, and it is that behavior – the things that happen, the things that the characters do and say, and the times and ways in which all of these occur – that ultimately defines the experience. The experience is created as a direct result of the AI’s ability (or inability) to evaluate the situation, make appropriate decisions, and deliver an appropriate performance (much like a stage actor’s performance) on the part of the characters and other gameplay elements. Or, to put it more succinctly, the AI is the game. It is the AI which drives behavior, and that behavior is an essential element of both effectiveness (i.e. how well the player learns) and engagement (i.e. how completely the player is drawn into the game). Recently there has been quite a bit of hype (and, in some cases, dread) around modern developments in AI, but the approaches used by games are quite different from those used in applications such as self-driving cars, speech recognition, cognitive modelling, or even world-class Go opponents. Nevertheless, the game AI community is vibrant, with numerous conferences, publications, and web sites. Over the past 15 to 20 years this community has made immense strides in techniques that can craft behavior that is appropriate to the particular type of game and the particular type of experience that is being envisioned by the game’s designers. At the same time, computers have become more capable, players have become more discerning, and games have become correspondingly more complex. With the increase in both expectations and complexity, it sometimes feels like a battle just to hold the line and deliver the same quality of experience that we achieved 20 years ago through simpler means! This talk will present the state of the art in Game AI. It will begin with a discussion of what Game AI is and how our goals differ from those of many other disciplines of AI. From there, it will give a whirlwind tour of problem areas and techniques to address each one. Along the way it will discuss not only what is solved, but also exciting areas for future work and what solutions in those spaces might look like, all the while maintaining a strong focus on those areas that are crucial in games for learning rather than just games for entertainment. Last, but certainly not least, the talk will provide references to major sources of material in this field.
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The AI is the Game Crafting the Behavior that Creates an Experience that Drives Learning Kevin Dill Senior Technical Staff Advanced Simulations Centers Lockheed Martin Rotary & Mission Systems kevin.dill@lmco.com
What is a Game • Something that's "fun?" Tic-Tac-Toe? Chess? StarCraft? Left4Dead? • • • • • Sid Meier: a series of interesting decisions • Raph Koster: Mastery
What is a Game • Experience • More than just “fun” Being There Teamwork Drama Character Angst • • • • • • The game is not the experience The experience is internal to the player It is *created* by the game It may not be the same for everyone • • •
Crafting an Experience • Art & Rendering Technology Game AI • Sound & Audio Technology • Game Design • What Stuff Does (i.e. the Behavior) How do characters interact? How do game mechanics respond to the player? How does content get picked? • • •
Putting the Ghost in the Machine • Ernest Adams, 1999 • An AI programmer is like a stage magician… • The illusion of intelligence • Suspension of disbelief
The First Rule of Game AI: • Don’t do anything stupid
What We Do [Fairly] Well • Architectures for Hand-Authored Behavior Behavior Trees Utility-Based AI Modular AI • • • • Spatial Reasoning Where am I, where is the enemy, where is safe, what do I control, where are chokepoints, … • • Path Planning & Motion Control Dynamic, handles formations, handles crowds, avoids obstacles, ... Climbing, running, jumping, diving, pointing, aiming, ... • • • Everything Combat Based!
Challenge Area: Why Not Just Use [Deep Learning] • Was Alpha Go a success? • Strengths: Classification "This is a Type 0x00c11a59 input..." "This is a Type 0x00c11a59 input, therefor if I return output 0x0155f873 I will maximize the score provided by my heuristic." • • • Weaknesses: Create a particular experience Act like a human Provide authorial control Risk – change management • • • • • Use it for what? • Can we achieve synergy?
Challenge Area: Adaptive Content • To engage students, don't bore them but also don't overwhelm • Evaluation Machine learning to determine user understanding, user engagement, user emotional state Common Core / Learning Maps • • • Execution Drama Managers: specify or select appropriate content Procedural Content Generation (PCG): generate or customize material Start small (e.g. hints, reminders) • • •
Challenge Area: Engaging Characters • How do we make the character like, trust, engage, emotionally connect with the characters in the game? Companions, Tutors, Assistants, Cultural Characters, etc. • • Thoughts: Characters must visibly be aware of and responsive to the environment Emotionally responsive, not just physically responsive Dynamic, AI-controlled, continuously believable affect (expression, stance, gesture, tone of voice) Characters must never be annoying Characters must be helpful Characters should engage with the player in a casual, but not annoying way • • • • • •
Challenge Area: Instructor Controls & Interaction • How do we enable an instructor (limited technical skills) to customize learning content, both before and during execution? • Thoughts: Careful consideration of what to expose, how to present PCG assistants Constraints Rapid auto-gen Customization after generation Plus the usual slew of instructor operation station & after action review tools • • • • • •
Resources • Game AI Pro series Free after 2 years: www.gameaipro.com Also AI Game Programming Wisdom series, Game Gems series, … • • • GDC AI Summit Free after 2 years: www.gdcvault.com • • AIGameDev.com Mix of free & pay: www.aigamedev.com •
The AI is the Game Crafting the Behavior that Creates an Experience that Drives Learning Kevin Dill Senior Technical Staff Advanced Simulations Centers Lockheed Martin Rotary & Mission Systems kevin.dill@lmco.com
AI is a Perception Problem • Dr. Kimberly Voll, 2015 Independent Games Summit GDC 2015 http://www.gdcvault.com/play/1022104/Less -is-More-Designing-Awesome • • • AI is a Perception Problem • Work with the brain The brain is a pattern matcher This is good and bad... The brain is a story teller It anthropomorphizes everything It creates its own narrative • • • • • • Start simple – Less is More “You can obscure intelligent behaviors that are naturally emerging if you go complex too fast.” •
