Computational Models of Motivation for Game-Playing Agents / by Kathryn E. Merrick.

Format:

Book

Author/Creator:

Merrick, Kathryn E., author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Language:

English

Subjects (All):

Artificial intelligence.

Computational intelligence.

Data mining.

Artificial Intelligence.

Computational Intelligence.

Data Mining and Knowledge Discovery.

Local Subjects:

Artificial Intelligence.

Computational Intelligence.

Data Mining and Knowledge Discovery.

Physical Description:

1 online resource (XVII, 213 pages) : 66 illustrations, 23 illustrations in color

Edition:

First edition 2016.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

System Details:

text file PDF

Summary:

The focus of this book is on three influential cognitive motives: achievement, affiliation, and power motivation. Incentive-based theories of achievement, affiliation and power motivation are the basis for competence-seeking behaviour, relationship-building, leadership, and resource-controlling behaviour in humans. In this book we show how these motives can be modelled and embedded in artificial agents to achieve behavioural diversity. Theoretical issues are addressed for representing and embedding computational models of motivation in rule-based agents, learning agents, crowds and evolution of motivated agents. Practical issues are addressed for defining games, mini-games or in-game scenarios for virtual worlds in which computer-controlled, motivated agents can participate alongside human players. The book is structured into four parts: game playing in virtual worlds by humans and agents; comparing human and artificial motives; game scenarios for motivated agents; and evolution and the future of motivated game-playing agents. It will provide game programmers, and those with an interest in artificial intelligence, with the knowledge required to develop diverse, believable game-playing agents for virtual worlds.

Contents:

From Player Types to Motivation

Computational Models of Achievement, Affiliation, and Power Motivation

Game Playing Agents and Non-player Characters

Achievement Motivation

Profiles of Achievement, Affiliation, and Power Motivation

Enemies

Pets and Partner Characters

Support Characters

Evolution of Motivated Agents

Conclusion and Future Work. .

Other Format:

Printed edition:

ISBN:

978-3-319-33459-2

9783319334592

Access Restriction:

Restricted for use by site license.