within the Games Industry by Jake Fudge

In-depth investigation of the applications an implications of AI throughout the games industry Focus on games made from 2000 onwards Uses of FL, NN and GA’s Covering across multiple platforms Discussing the Middleware market Discussion of hardware (i.e. PCI-E & Multicore CPUs) Chart the progression of the industry (i.e. CPU -> GPU) Case studies on Source and Gamebryo engines (i.e. Oblivion)

In-depth investigation of the applications an implications of AI throughout the games industry

Focus on games made from 2000 onwards

Uses of FL, NN and GA’s

Covering across multiple platforms

Discussing the Middleware market

Discussion of hardware (i.e. PCI-E & Multicore CPUs)

Chart the progression of the industry (i.e. CPU -> GPU)

Case studies on Source and Gamebryo engines

(i.e. Oblivion)

Control – motor controller, for example, control of a race car or airplane Threat Assessment – input number of enemy ground units, aerial units, etc. Attack or Flee – input health, distance to enemy, class of enemy, etc. Anticipation – Predicting player’s next move, input previous moves, output prediction E.g. Black & White – uses NN’s to train behaviour through ‘tickling’ and ‘ smacking’ to increase/decrease weights

Control – motor controller, for example, control of a race car or airplane

Threat Assessment – input number of enemy ground units, aerial units, etc.

Attack or Flee – input health, distance to enemy, class of enemy, etc.

Anticipation – Predicting player’s next move, input previous moves, output prediction

E.g. Black & White – uses NN’s to train

behaviour through ‘tickling’ and

‘ smacking’ to increase/decrease weights

Constructed with the simple aim of keeping the car to the racing line Used standard feedforward multilayer perceptron neural network

Constructed with the simple aim of keeping the car to the racing line

Used standard feedforward multilayer perceptron neural network

Fuzzy logic represents facts as a matter of degree rather than true/false statements Humans often assign facts to categories with some flexibility about the boundary conditions In control applications, like Game AI, responses to fuzzy input are smooth Traditional Boolean logic only supports discrete states often resulting in abrupt state transitions Fuzzy logic avoids these problems because the response will vary smoothly given the degree of truth of input conditions E.g. Control – locomotion control that responds smoothly to obstacles Threat Assessment - assessment of the threat posed by players/opponents Classification - in-game classification of characters and game scenarios Spark! Fuzzy Logic Editor (by Louder Than A Bomb! software)

Fuzzy logic represents facts as a matter of degree rather than true/false statements

Humans often assign facts to categories with some flexibility about the boundary conditions

In control applications, like Game AI, responses to fuzzy input are smooth

Traditional Boolean logic only supports discrete states often resulting in abrupt state transitions

Fuzzy logic avoids these problems because the response will vary smoothly given the degree of truth of input conditions

E.g. Control – locomotion control that responds smoothly to obstacles

Threat Assessment - assessment of the threat posed by players/opponents

Classification - in-game classification of characters and game scenarios

Spark! Fuzzy Logic Editor

(by Louder Than A Bomb! software)

Excellent for tuning in-game parameters E.g. Counter Strike: Source™ weapons Mainly found to be used in preprocessing Cons - Limited use outside of this

Excellent for tuning in-game parameters

E.g. Counter Strike: Source™ weapons

Mainly found to be used in preprocessing

Cons - Limited use outside of this

AI GUI Visual toolbox Allows developers to concentrate on design rather than programming Modular design (AI building blocks) C++ editor Extended features Procedural animation Interactive dialogue Use of Spir.Ops AI can be found in Splinter Cell: Double Agent (Xbox 360/PC/PS3)

AI GUI

Visual toolbox

Allows developers to concentrate on design rather than programming

Modular design (AI building blocks)

C++ editor

Extended features

Procedural animation

Interactive dialogue

Radiant AI SpeechCraft – allows for creative dialogue through visual cues NPC’s given a schedule which they have to achieve (sometime by any means possible!) Skills and Race of character determine what information is available Active AI based off skill to create more challenge (i.e. stronger rats)

Radiant AI

SpeechCraft – allows for creative dialogue through visual cues

NPC’s given a schedule which they have to achieve (sometime by any means possible!)

Skills and Race of character determine what information is available

Active AI based off skill to create more challenge (i.e. stronger rats)

Coarse – started by splitting client-side and server-side systems Disparity within the engine Fine – breaking up tasks into tiny pieces for equal distribution (similarities to Distributed Computing) More complex than coarse threading Bound by memory bandwidth Hybrid – more of a system hierarchy than a new method

Coarse – started by splitting client-side and server-side systems

Disparity within the engine

Fine – breaking up tasks into tiny pieces for equal distribution (similarities to Distributed Computing)

More complex than coarse threading

Bound by memory bandwidth

Hybrid – more of a system

hierarchy than a new

method

Nintendo™ Wii-mote Gesture based gaming Computational limitations on motion capturing Programming actions through neural networks Can accepts large database of actions

Nintendo™ Wii-mote

Gesture based gaming

Computational limitations on motion capturing

Programming actions through neural networks

Can accepts large database of actions