This novel reassessment of the field presents the central concepts in evolutionary game theory and provides an authoritative and up-to-date account. The focus is on concepts that are important for biologists in their attempts to explain observations. This strong connection between concepts and applications is a recurrent theme throughout the book.
This novel reassessment of the field presents the central concepts in evolutionary game theory and provides an authoritative and up-to-date account. The focus is on concepts that are important for biologists in their attempts to explain observations. This strong connection between concepts and applications is a recurrent theme throughout the book.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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Autorenporträt
John McNamara is Emeritus Professor of Mathematics and Biology at the University of Bristol, UK. After competing his doctorate on black holes in 1976, he changed his research focus to animal behaviour and evolutionary biology. In these fields he has developed approaches to modelling behaviour, particularly approaches based on state variables. In studying animal behaviour his objective has been to provide theoretical explanations of known phenomena and to motivate and steer the direction of new experiments. Areas in which he has contributed include foraging theory, life history theory, and game theory. Olof Leimar is Emeritus Professor of Zoology at Stockholm University, Sweden. After studying theoretical physics in Stockholm, he switched to biology and completed his doctorate in 1988 with a thesis on game-theory analysis of animal fighting. In modelling animal behaviour, he introduces behavioural mechanisms, including mechanisms from learning psychology to achieve greater biological realism. In addition to fighting behaviour, he has applied this approach to the evolution of warning colouration and mimicry. Other fields he has worked in include sex allocation, mutualism, life-history theory, developmental plasticity and phenotype determination. He develops mathematical models, but he has also been involved in experimental work in his areas of interest.
Inhaltsangabe
1: Setting the scene 2: Central concepts 3: Standard examples 4: Stability concepts: beyond Nash equilibria 5: Learning in large worlds 6: Co-evolution of traits 7: Variation, consistency, and reputation 8: Interaction, negotiation, and learning 9: Games embedded in life 10: Games over generations 11: Future perspectives Appendix A: Summary of notation Appendix B: Solutions to exercises
1: Setting the scene 2: Central concepts 3: Standard examples 4: Stability concepts: beyond Nash equilibria 5: Learning in large worlds 6: Co-evolution of traits 7: Variation, consistency, and reputation 8: Interaction, negotiation, and learning 9: Games embedded in life 10: Games over generations 11: Future perspectives Appendix A: Summary of notation Appendix B: Solutions to exercises
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