AI challenges in
Entertainment and Player Expression
Doug Church
AIIDE
1 June 2005
Who Am I
• Programmer by Schooling
• Designer/Programmer by Training/Practice
• Interested in Technology enabling Design
Worked on (i.e. coded, designed) a bunch of old
PC games, recently have been doing highlevel goal setting/evaluation of (i.e. not real
work) a variety of console games
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This Talk
Initially hoping to do an end-of-week recap kind
of thing, discussing trends I saw over the
course of the conference and relating them to
current industry situations
But turned out I was speaking first
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So...
Instead, I’ll talk about
• AI related game design challenges I find most
interesting as we head to next generation
• My perception of how the state of the industry
impacts AI work going forward
This is a game design talk more than an AI talk
Primary focus on single player games
There are no pretty demos or pictures... sorry
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Topics and Takeaways
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Changing landscape in games space
How biz model messes with AI evolution
Rise of entertainment content
What experiences are we providing
Opportunities/approaches for meaningful
forward steps in the industry, risks
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Context
Much is changing in the industry
Changes in Market
• Growing gap between top-sellers and the rest
• Growing budgets and team size
• Clear hook, 30 second experience pitch
• Promise of direct distribution/ability to hit
smaller markets with indie titles remains on
the horizon, unfulfilled, but still discussed
• Indie market would mean a very different talk
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Changes in Development
• Content the real issue (budget, time, quality)
– Most games now content led not tech led
– Data driven everything in order to get done
– Get programmer out of way, tight feedback loop
• Team scale impacting process, creativity
– Getting everyone on same page
– Creatively collaborate at large scale
• Less discipline-based, more task-oriented
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Changes in Gaming
• For many years games were linear
sequences of challenges
– challenge itself as play-value/entertainment
– “world” abstracted and simplified
• Current trends
– high world fidelity, and growing
– open-ended worlds, player choice/customization
– entertainment aspects/pacing, characters
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Changes in Fidelity
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Graphics: huge leaps in 20 years
Scale and density of environments increasing
Physics fidelity obviously much better
Even design has several new “common
styles” of play (trading/collectibles, openworld mission stacks, etc...)
• Conversation systems? not so much...
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Changing Players
• Online (XBox Live, etc) providing more multihuman gaming opportunities
• MMO’s growing in popularity, providing large
environments for “meaningful” player action
• Single-player games containing more movieinspired moments, more watching
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The Mainstream Industry
Getting Games Made
The Industry Now
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Consolidation: Fewer games, bigger budgets
Harder to get projects started, approved
Risk management central to business
Large public companies revenue driven, need
big sales numbers regardless of dev cost
• Licensing IP from other media, or sequel-ing
established IPs, major part of forward plan
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Evaluating Games
• Player Fantasy: what experience is being
delivered for the player
• Key Pillars: game feature hooks for players to
get excited about and promise play value
• Uniqueness: competitive landscape
• Reality Check: can it be done? on time?
– market windows, competitive product timelines,
budget analysis, dev team experience, etc...
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Relevance to AI
• Improved cover finding is very nice
• Guys who don’t get stuck on corners are nice
• Non-magical following of a racing line is nice
... none of these makes much of a 30 second
TV ad, or a quick sound byte for Newsweek
... and if the character only lives for a minute,
how much fidelity can we even perceive
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Market Reality
• Tons of interesting and hard work goes into
making modern game AI’s able to work at all
– but it is expected by the market, and really is
mentioned most when it fails, not succeeds
• Even in specialist press, we’ve basically
bragged our way out of meaningful claims
– “realistic characters respond to your actions” has
been said for 10+ years about games
– and often scripted stuff has more impact/is
remembered more by players
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The Result
• AI code can be hard to build, and innovating
and improving it is seen as risky
– So potentially valuable/interesting features often
cut as scope/risk reduction
• Press/users outcry for better AI usually trivial
– i.e. pathing and grenade dodging kind of things
– hard work, sure, but not some new innovation
• Hard to make case for future looking AI
investment given risk profile and low ROI
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That Said
• Consumers do get excited when something
combines new AI with new play idea/concept
– Black and White, The Sims, first RTS games
– Many of these had struggles to approve/release
• Can we encourage/enable more of that?
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What is needed to Pitch it?
• Attach AI feature to compelling player fantasy
• Identify and show a unique player
experience/mechanic the AI feature enables
• Some other pain point of development (cost,
time) that the AI technique will improve
• Evidence it wont require leaping off some 10year research project cliff into total unknown
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Technology Status
What challenges?
What can we do?
AI Tech Situation
• As fidelity of worlds (graphic environment
detail, lighting, terrain complexity) grows,
challenge of just keeping up ratchets up
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pathing on a 2d tilemap with 90 degree walls easy
pathing on an arbitrary polygon mesh, not as easy
switching between idle and combat sprites easy
managing 100+ bone blended model, not as easy
and so on...
• Just keeping old features working is hard
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Some example AI Tech
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Pathfinding
Map Analysis (cover, opportunity, shortcut)
Group coordination and management
Actions (climb rope, fire gun, plus world use)
Expression (what do i say, what anims...)
Senses
Traits and Characterizations
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Some example AI Tech
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Pathfinding
Map Analysis (cover, opportunity, shortcut)
Group coordination and management
Actions (climb rope, fire gun, plus world use)
Expression (what do i say, what anims...)
Senses
Traits and Characterizations
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Enabling Players
• Unique DNA of gaming is interaction
• Currently, we provide lots of microinteractions (move, shoot, dodge)
• Lack of support for larger scale player choice
• Hence drive towards online (where other
humans provide the reaction to the choices)
• AI is the obvious tool to enable more player
flexibility and expression
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Who Cares?
• Plenty of games are fine w/current level of
expression (Tetris works pretty well, etc...)
• And movie style games are plenty fun
• But we are missing out on a huge range of
possibilities, and ones that are uniquely us
• More reactive worlds with more payoffs and
meaning to choices will be more human
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Entertainment Aspects
• Big moment payoff in FPS these days rarely
comes straight from the systems/AI core
– scipted overrides with hand-placed triggers/events
– AI core supports the set piece by moving actors
about, reacting and sensing, but that is it
• Similarly in many other types... AI controls the
mundane character actions, and then in big
events the character is put into auto-pilot
• Pure systems behavior often seen as flat
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Entertainment and Reality
• Often as our AI’s/NPC setups get better, they
become worse as game foils
– hard to tell what is going on, why
– opaque actions, no sense of agency
• Need better demonstrations of NPC traits
– emotes, drawing attention, some sort of feedback
• AI needed to support director’s goals and
feel, not impose reality
– AI to help pacing, variety, etc... lots to try
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AI in Games
What are we using this for?
AI Styles we use a lot
• Opponent
– Simulates another human player
– i.e. enemy fighter in SC, general in an RTS, etc
• Manage
– Simulates independent agents to attempt to direct
– i.e. RTS troops, Sims in the Sims, B&W creature
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Why these styles
• Opponent
– Strategize against player abilities
– Pick challenges (shoot a guy who is in cover,
chase a guy, drive faster than guy) and build AI
around that optimization goal
• Manage
– Build systems based AIs with limited but
repeatable capabilities
– Gameplay about player learning to use them
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Styles and Expression
• Opponent and Manage provide clear
expression for player in micro-actions taken
• Presented sequence of small goals, have
freedom on how to get there using toolset
• Often provide a very small-task oriented
approach to completion
• Much like a job or homework... checklists
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Styles we do not use much
• Negotiate
– limited use in RTS environments
• Converse
– very very limited conversation tree models,
primarily, almost universally prescripted branching
• Choice and Consequence
– Occasional forays into faction based/multiple valid
path, but mostly still save and reload based play
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Steps toward other styles
• Mercenaries
– very basic faction model, and somewhat opaque
and low on consequence (at least for first several
hours), but still has NPC reactions to player choice
• Fable
– very shallow NPCs, but they pay attention to
player actions and shade their opinion/behavior
• Nintendogs
– Ok, just another pet sim, but it is non-combat
character interaction, and a nice “step” on a path
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Design Challenges
• Growing AI complexity makes expression
harder in some ways
– what were they reacting to? did what i do matter?
– is he my friend or did he just not see me or am i
wearing a disguise or maybe...
• Add a complex behavioral/sensory model and
getting meaningful player feedback is tough
• Another reason pure opponent model is nice
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Design Needs
• What tools address this, can designers use
them, what feedback do they get?
• Tension between automated response and
precise controls, where is sweet spot?
• AI’s need to be Robust, Contextually aware,
and Controllable... not an easy balance
• Esp. as world systems grow in complexity
• Getting good at this for micro-tactical combat
setups... but not much for levels above this
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Going Forward
What are we doing?
Optimistic View
• Keeping up, AI can manage characters in
increasingly complex settings
• Games to keep moving forward
• Complex settings give options for expression
• More scope for entertainment as we can
create more compelling and full worlds
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Pessimistic View
• Existing trajectory continues to evolve a small
set of games, ignoring many more
– Great, we master low-level tactics
– No player-driven character interactions, scripting
the choice for memorable entertainment moments
• Single player games become movies with
tactical/combat/physics challenges to “turn
the page” to the next scene
• Single player as “training dummies” for online
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Proactive Response
• Reality somewhere in the middle
• Can’t wait for more interesting AI integration
and adoption to “just happen”
• Need to address current industry needs
(entertainment, risk management) w/o giving
up on pushing other AI types
• Note: Nothing wrong with better pathing/etc,
but is that all we can do?
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So we need to get ahead
• Finally good at doing games in Year 2000
– 20 person teams, static worlds, a few characters
– Ooops, a bit late, eh?
• Where do we need to get ahead
– Tools: get on par with graphics/world fidelity
• middleware? more sharing of tech ideas?
– Tools: better blend of AI systems behaviors and
“script-like” entertainment elements...
– Risk: need manageable steps, solid path
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Some Pain Points to address
• Dev Costs
– w/o better AI tools won’t be able to build content,
due to pain of path management and scripting
• Necessity of more complex worlds
– if-then structures will become unmanageable, get
more flexible and robust solutions going now
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Opportunities to go for
• New styles
– Hard to make them work, but when you do, and
connect them to a market, you are very happy
• “Real AI” – planning, learning
– manageable but meaningful steps into games
• Entertainment
– flexibility to allow big moments to be attached to
real choices would be very compelling
– Take gaming big moments back from the movie
people, make them interactive
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The End