Verfügbarkeit: On the design of game-playing agents | Technische Universität München

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Bibliographische Detailangaben
Beteiligte Personen:	Kim, Eun-Youn (VerfasserIn), Ashlock, Daniel 1961- (VerfasserIn)
Format:	Buch
Sprache:	Englisch
Schriftenreihe:	Synthesis lectures on games and computational intelligence 2
Schlagwörter:	Computerspiel Computersimulation Agent > Informatik
Links:	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030487041&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030487041&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
Umfang:	xiii, 172 Seiten Illustrationen, Diagramme
ISBN:	9781681731629

Internformat

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Datensatz im Suchindex

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adam_text	Vll /O Ia . . t W •liL a !■ GJ Preface.....................................................................xi Acknowledgments...........................................................xiii 1 Introduction.................................................................1 1.1 Prisoner s Dilemma and Other Games....................................3 1.2 Digital Evolution: Evolving Game Players...............................4 1.2.1 Optimization vs. Co-evolution...................................5 1.3 From Checkers through the Rise of the Go Machines.....................6 1.4 Why are the Simple Games so Hard?.....................................7 2 The First Place Where Trouble Arose..........................................9 2.1 Representation—What Is It?.............................................9 2.1.1 Finite State Machines, Direct Representation...................10 2.1.2 Finite State Machines with a Cellular Representation...........12 2.1.3 Boolean Primulas...............................................14 2.1.4 Function Stacks................................................15 2.1.5 ISAc Lists.....................................................16 2.1.6 Markov Chains and Look-up Tables........................... 17 2.1.7 Artificial Neural Nets.........................................17 2.2 Fingerprinting—A Tool for Comparing Across Representations............19 2.2.1 Definition of Fingerprints.....................................19 2.2.2 Example Fingerprint Computation................................20 2.2.3 Fingerprint Results............................................21 2.3 The Uncontrolled Variable Discovery...................................24 2.3.1 Experimental Design ...........................................24 2.3.2 Experimental Results ..........................................25 2.3.3 Conclusion.....................................................30 3 Problems Beyond Representation..............................................33 3,1 Changing the Payoff Matrix Changes the Agents that Arise..............33 3.1.1 Design of Experiments..........................................34 Vlll 3.1.2 Results and Discussion...........................................37 3.1.3 Conclusions......................................................42 3.2 Changing the Level of Resources........................................44 3.2.1 Design of Experiments............................................45 3.2.2 Results and Discussion...........................................52 3.2.3 Conclusions and Next Steps.......................................62 3.3 Algorithm Details Matter To Population Size, Elite Fraction, and Mutation Rate .........................................................64 3.3.1 Design of Experiments............................................65 3.3.2 Results and Discussion...........................................68 3.3.3 Conclusions and Next Steps.......................................72 3.4 Including Tags and Geography...........................................74 3.4.1 Grid-based nIPD and Agent Specifications ........................75 3.4.2 Experimental Design .............................................78 3.4.3 Results..........................................................79 3.4.4 Conclusions......................................................85 4 Does All This Happen Outside of Prisoner s Dilemma?.........................87 4.1 Coordination Prisoners Dilemma, Rock-Paper-Scissors, and Morphs........87 4.1.1 Design of Experiments............................................89 4.1.2 Results and Discussion...........................................93 4.1.3 Conclusions......................................................99 4.2 Divide-the-Dollar—A More Complex Game.................................101 4.2.1 Generalize Divide-the-Dollar....................................103 4.2.2 Design of Experiments...........................................106 4.2.3 Results and Discussion..........................................108 4.2.4 Conclusions and Next Steps......................................112 4.3 The Snowdrift Game....................................................114 4.3.1 The Game Models.................................................115 4.3.2 Experimental Results............................................119 4.3.3 Discussion......................................................122 4.3.4 Conclusions.....................................................126 5 Noise!......................................................................127 5.1 Noisy Games are Different ...........................................127 5.1.1 Experimental Design ............................................128 5.1.2 Analysis Techniques.............................................128 IX 5.1.3 Results and Discussion..........................................132 5.1.4 Conclusions and Next Steps......................................139 5,2 Evolutionary Velocity.................................................141 5.2.1 Definition of Evolutionary Velocity.............................142 5.2.2 Analysis of Evolutionary Velocity...............................142 6 Describing and Designing Representations....................................149 6.1 Does the Representation have Internal States?.........................150 6.2 Does the Representation use External State Information?...............151 6.3 Can the Representation Learn?.........................................153 6.4 Does the Representation use Random Numbers?...........................154 6.5 Complex Representations ..............................................155 Bibliography...............................................................161 Authors’ Biographies.......................................................171 Series Editor: Daniel Ashlock, University of Guelph On the Design of Game-Playing Agents Eun-Youn Kim, Hanbat National University Daniel Ashlock, University of Guelph Evolving agents to play games is a promising technology. It can provide entertaining opponents for games like Chess or Checkers, matched to a human opponent as an alternative to the perfect and unbeatable opponents embodied by current artificial intelligences. Evolved agents also permit us to explore the strategy space of mathematical games like Prisoner’s Dilemma and Rock-Paper- Scissors. This book summarizes, explores, and extends recent work showing that there are many unsuspected factors that must be controlled in order to create a plausible or useful set of agents for modeling cooperation and conflict, deal making, or other social behaviors. The book also provides a proposal for an agent training protocol that is intended as a step toward being able to train humaniform agents—in other words, agents that plausibly model human behavior. ABOUT SYNTHESIS This volume is a printed version of a work that appears in the Synthesis Digital Library of Engineering and Computer Science. Synthesis lectures provide concise original presentations of important research and development topics, published quickly in digital and print formats. For more information, visit our website: http://store.morganclaypool.com
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series	Synthesis lectures on games and computational intelligence
series2	Synthesis lectures on games and computational intelligence
spellingShingle	Kim, Eun-Youn Ashlock, Daniel 1961- On the design of game-playing agents Synthesis lectures on games and computational intelligence Computerspiel (DE-588)4010457-6 gnd Computersimulation (DE-588)4148259-1 gnd Agent Informatik (DE-588)4455835-1 gnd
subject_GND	(DE-588)4010457-6 (DE-588)4148259-1 (DE-588)4455835-1
title	On the design of game-playing agents
title_auth	On the design of game-playing agents
title_exact_search	On the design of game-playing agents
title_full	On the design of game-playing agents Eun-Youn Kim, Daniel Ashlock
title_fullStr	On the design of game-playing agents Eun-Youn Kim, Daniel Ashlock
title_full_unstemmed	On the design of game-playing agents Eun-Youn Kim, Daniel Ashlock
title_short	On the design of game-playing agents
title_sort	on the design of game playing agents
topic	Computerspiel (DE-588)4010457-6 gnd Computersimulation (DE-588)4148259-1 gnd Agent Informatik (DE-588)4455835-1 gnd
topic_facet	Computerspiel Computersimulation Agent Informatik
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