AI challenges inEntertainment and Player Expression

Doug Church

AIIDE

1 June 2005

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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 high-level 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

• 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

Context

Much is changing in the industry

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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

• 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, open-world mission stacks, etc...)

• Conversation systems? not so much...

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Changing Players

• Online (XBox Live, etc) providing more multi-human gaming opportunities

• MMO’s growing in popularity, providing large environments for “meaningful” player action

• Single-player games containing more movie-inspired moments, more watching

The Mainstream Industry

Getting Games Made

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The Industry Now

• 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 10-

year research project cliff into total unknown

Technology Status

What challenges?

What can we do?

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AI Tech Situation

• As fidelity of worlds (graphic environment detail, lighting, terrain complexity) grows, challenge of just keeping up ratchets up– 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

• 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

• 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 micro-

interactions (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

AI in Games

What are we using this for?

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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

Going Forward

What are we doing?

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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

The End