Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Learning automata: an introduction
Learning automata: an introduction
A Bayesian model of plan recognition
Artificial Intelligence
Evolutionary dynamics of spatial games
Proceedings of the NATO advanced research workshop and EGS topical workshop on Chaotic advection, tracer dynamics and turbulent dispersion
Negotiation and cooperation in multi-agent environments
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
Journal of Intelligent and Robotic Systems
Evolution of Signaling in a Multi-Robot System: Categorization and Communication
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
A probabilistic plan recognition algorithm based on plan tree grammars
Artificial Intelligence
Learning to coordinate in complex networks
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Intention-based decision making with evolution prospection
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
The emergence of commitments and cooperation
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
State-of-the-art of intention recognition and its use in decision making
AI Communications
Intelligent Decision Technologies
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Few problems have created the combined interest of so many unrelated areas as the evolution of cooperation. As a result, several mechanisms have been identified to work as catalyzers of cooperative behavior. Yet, these studies, mostly grounded on evolutionary dynamics and game theory, have neglected the important role played by intention recognition in behavioral evolution. Here we address explicitly 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 then able to predict the next move of their opponents based on past direct interactions, which, in turn, enables them to prevail over the most famous strategies of repeated dilemmas of cooperation, even in presence of noise. Overall, our framework offers new insights on the complexity and beauty of behavioral evolution driven by elementary forms of cognition.