Coordination in multiagent reinforcement learning: a Bayesian approach
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Autonomous Robots
Bayesian Reinforcement Learning for Coalition Formation under Uncertainty
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
A probabilistic language based upon sampling functions
Proceedings of the 32nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Coalition formation under uncertainty: bargaining equilibria and the Bayesian core stability concept
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
An ontology-based approach to interoperability for Bayesian agents
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
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Autonomous intelligent agents paradigm has encouraged robotic researches to take another step forward in the design of control architectures replacing modules with agents. This paper presents a logical fusion between Bayesian theory and artificial intelligent agents, showing a new intelligent Bayesian agent architecture oriented towards Bayesian robotics. To define this architecture we will provide a common framework for developing intelligent agent applications using Bayesian theory. We will also review some of the most important Bayesian agent applications and we will compare them with our model. Finally, a simple robotic application will be provided as a proof of concept of the presented architecture.