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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

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Ai challenges in entertainment and player expression

AI challenges inEntertainment and Player Expression

Doug Church


1 June 2005

Who am i
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


This talk
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


Ai challenges in entertainment and player expression

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


Topics and takeaways
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




Much is changing in the industry

Changes in market
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


Changes in development
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


Changes in gaming
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


Changes in fidelity
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...


Changing players
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

The Mainstream Industry

Getting Games Made

The industry now
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


Evaluating games
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...


Relevance to ai
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


Market reality
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


The result
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


That said
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?


What is needed to pitch it
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

Technology Status

What challenges?

What can we do?

Ai tech situation
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


Some example ai tech
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


Some example ai tech1
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


Enabling players
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


Who cares
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


Entertainment aspects
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


Entertainment and reality
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

AI in Games

What are we using this for?

Ai styles we use a lot
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


Why these styles
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


Styles and expression
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


Styles we do not use much
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


Steps toward other styles
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


Design challenges
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


Design needs
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

Going Forward

What are we doing?

Optimistic view
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


Pessimistic view
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


Proactive response
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?


So we need to get ahead
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


Some pain points to address
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


Opportunities to go for
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