Computational models of motivation for game playing agents / Kathryn E. Merrick.

Preface; Part I-Game Playing in Virtual Worlds by Humans and Agents; Part II-Comparing Human and Artificial Motives; Part III-Game Scenarios for Motivated Agents; Part IV-Evolution and the Future of Motivated Agents; Contents; Symbols and Acronyms; List of Algorithms; Game Playing in Virtual Worlds by Humans and Agents; 1 From Player Types to Motivation; 1.1 Virtual Worlds and Online Games; 1.2 Explorer, Achiever, Socialiser, Aggressor: Human Player Types; 1.3 Incentive-Based Theories of Motivation; 1.3.1 Incentive; 1.3.2 Achievement Motivation; 1.3.3 Affiliation Motivation

1.3.4 Power Motivation1.3.5 Dominant Motives and Motive Profiles; 1.3.6 Motivation and Zeitgeist; 1.4 Conclusion; References; 2 Computational Models of Achievement, Affiliation and Power Motivation; 2.1 Towards Computational Motivation; 2.2 Modelling Incentive-Based Motives Using Approach-Avoidance Theory; 2.2.1 Modelling Achievement Motivation; 2.2.2 Modelling Affiliation Motivation; 2.2.3 Modelling Power Motivation; 2.3 Motive Profiles for Artificial Agents; 2.3.1 Modelling Profiles of Achievement, Affiliation and Power; 2.3.2 Modelling the Dominant Motive Only

2.3.3 Optimally Motivating Incentive2.4 Using Motive Profiles for Goal Selection; 2.4.1 Winner-Takes-All; 2.4.2 Probabilistic Goal Selection; 2.5 Summary; References; 3 Game-Playing Agents and Non-player Characters; 3.1 Artificial Intelligence in Non-player Characters; 3.2 Rule-Based Agents; 3.2.1 Game Scenarios for Motivated Rule-Based Agents; 3.2.2 Motivated Rule-Based Agents; 3.3 Crowds; 3.3.1 Motivated Crowds; 3.4 Learning Agents; 3.4.1 Social Dilemma Games; 3.4.2 Strategies in Game Theory; 3.4.3 Motivated Learning Agents; 3.5 Evolution; 3.5.1 Multiplayer Social Dilemma Games

3.5.2 Evolution in Multiplayer Social Dilemma Games 3.5.3 Evolution of Motivated Agents; 3.5.3.1 Evolution of Motivated Agents using Objective Fitness; 3.5.3.2 Evolution of Motivated Agents using Subjective Fitness; 3.6 Summary; References; Comparing Human and Artificial Motives; 4 Achievement Motivation; 4.1 Scenarios and Mini-games for Motivated Agents; 4.2 The Ring-Toss Game; 4.3 Modelling Achievement-Motivated Rule-Based Agents; 4.4 AchAgents Playing the Ring-Toss Game; 4.4.1 Comparison to Humans; 4.4.2 Comparison to Atkinson's Risk-Taking Model

4.4.3 Comparison to a Model of Achievement Motivation with Learning4.5 Conclusion; References; 5 Profiles of Achievement, Affiliation and Power Motivation; 5.1 Evolving Motivated Agents to Play Multiple Games; 5.2 Roulette; 5.2.1 Motive Profiles for Roulette; 5.2.2 Motivated Rule-Based Agents Playing Roulette; 5.2.3 Comparison to Humans; 5.3 The Prisoners' Dilemma Game; 5.3.1 Motivated Rule-Based Agents and the Prisoners' Dilemma; 5.3.2 Comparison to Humans; 5.4 Conclusion; References; Game Scenarios for Motivated Agents; 6 Enemies; 6.1 Types of Non-player Characters and Their Roles