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Title:
Intention Recognition Promotes The Emergence of Cooperation
Publication date:
August 2011
Citation:
adap-behav11
Abstract:
Few problems have combined the interest of so many unrelated areas as the evolution of cooperation. Several mechanisms have been identified to catalyze cooperative behavior. These, mostly grounded on evolutionary dynamics and game theory, neglect the role played by intention recognition in behavioral evolution. We address this issue, characterizing the dynamics emerging from a population of intention recognizers. We derive a Bayesian Network model for intention recognition in the context of repeated social dilemmas and evolutionary game theory, by assessing the internal dynamics of trust between intention recognizers and their opponents. Intention recognizers are able to predict the next move of their opponents based on past direct interactions, in turn enabling them to prevail over the most famous strategies of repeated dilemmas of cooperation, even in presence of noise. We offer new insights on the complexity of behavioral evolution driven by elementary forms of cognition.
Journal
Authors:
Han The Anh
,
Luís Moniz Pereira
,
Francisco C. Santos
Journal:
Adaptive Behavior
Publisher:
Sage Publications
Address:
http://www.isab.org/journal/
Volume:
19
Number:
3
Pages:
264-279
ISBN:
-
ISSN:
1059-7123
Note:
-
Url address:
http://centria.di.fct.unl.pt/~lmp/publications/online-papers/IR_EvolutionOfCooperation%20.pdf
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Plain text:
Han The Anh and Luís Moniz Pereira and Francisco C. Santos, Intention Recognition Promotes The Emergence of Cooperation, Adaptive Behavior, Vol. 19, No. 3, Pag. 264-279, Sage Publications, http://www.isab.org/journal/, ISSN 1059-7123, (http://centria.di.fct.unl.pt/~lmp/publications/online-papers/IR_EvolutionOfCooperation%20.pdf), August 2011.
HTML:
<b><a href="/people/members/view.php?code=cdc7090d1f84f56c0671baa36e87bd77" class="author">Han The Anh</a>, <a href="/people/members/view.php?code=6175f826202ff877fba2ad77784cb9cb" class="author">Luís Moniz Pereira</a> and <a href="/people/members/view.php?code=ecbe12c4c0d80a28bae741293af61956" class="author">Francisco C. Santos</a></b>, <u>Intention Recognition Promotes The Emergence of Cooperation</u>, Adaptive Behavior, Vol. 19, No. 3, Pag. 264-279, Sage Publications, http://www.isab.org/journal/, ISSN 1059-7123, (<a href="http://centria.di.fct.unl.pt/~lmp/publications/online-papers/IR_EvolutionOfCooperation%20.pdf" target="_blank">url</a>), August 2011.
BibTeX:
@article {adap-behav11, author = {Han The Anh and Lu\'{\i}s Moniz Pereira and Francisco C. Santos}, title = {Intention Recognition Promotes The Emergence of Cooperation}, journal = {Adaptive Behavior}, publisher = {Sage Publications}, address = {http://www.isab.org/journal/}, volume = {19}, number = {3}, pages = {264-279}, issn = {1059-7123}, url = {http://centria.di.fct.unl.pt/~lmp/publications/online-papers/IR_EvolutionOfCooperation%20.pdf}, abstract = {Few problems have combined the interest of so many unrelated areas as the evolution of cooperation. Several mechanisms have been identified to catalyze cooperative behavior. These, mostly grounded on evolutionary dynamics and game theory, neglect the role played by intention recognition in behavioral evolution. We address this issue, characterizing the dynamics emerging from a population of intention recognizers. We derive a Bayesian Network model for intention recognition in the context of repeated social dilemmas and evolutionary game theory, by assessing the internal dynamics of trust between intention recognizers and their opponents. Intention recognizers are able to predict the next move of their opponents based on past direct interactions, in turn enabling them to prevail over the most famous strategies of repeated dilemmas of cooperation, even in presence of noise. We offer new insights on the complexity of behavioral evolution driven by elementary forms of cognition.}, keywords = {Evolution of Cooperation, IntentionIntention Recognition, Bayesian Networks, Evolutionary Game Theory}, month = {August}, year = {2011}, }
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