Explanation-based learning: a survey of programs and perspectives
ACM Computing Surveys (CSUR)
Classifier systems and genetic algorithms
Artificial Intelligence
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Instance-Based Learning Algorithms
Machine Learning
Case-based reasoning
Decision Tree Induction Based on Efficient Tree Restructuring
Machine Learning
JAM: a BDI-theoretic mobile agent architecture
Proceedings of the third annual conference on Autonomous Agents
Machine Learning
Autonomous Agents and Multi-Agent Systems
Machine Learning
Explanation-Based Learning: An Alternative View
Machine Learning
Learning in multi-agent systems
The Knowledge Engineering Review
Learning probabilistic networks
The Knowledge Engineering Review
Distributed Learning in Intentional BDI Multi-Agent Systems
ENC '04 Proceedings of the Fifth Mexican International Conference in Computer Science
Cooperative Multi-Agent Learning: The State of the Art
Autonomous Agents and Multi-Agent Systems
Evolutionary game theory and multi-agent reinforcement learning
The Knowledge Engineering Review
Hierarchical planning in BDI agent programming languages: a formal approach
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Programming Multi-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology)
Programming Multi-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology)
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
The PELA architecture: integrating planning and learning to improve execution
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Decision-making in an embedded reasoning system
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Learning in BDI multi-agent systems
CLIMA IV'04 Proceedings of the 4th international conference on Computational Logic in Multi-Agent Systems
Learning within the BDI framework: an empirical analysis
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Learning context conditions for BDI plan selection
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Extending BDI plan selection to incorporate learning from experience
Robotics and Autonomous Systems
Generating inspiration for agent design by reinforcement learning
Information and Software Technology
Reinforcement learning as heuristic for action-rule preferences
ProMAS'10 Proceedings of the 8th international conference on Programming Multi-Agent Systems
Integrating learning into a BDI Agent for environments with changing dynamics
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
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Belief, Desire, and Intentions (BDI) agents are well suited for complex applications with (soft) real-time reasoning and control requirements. BDI agents are adaptive in the sense that they can quickly reason and react to asynchronous events and act accordingly. However, BDI agents lack learning capabilities to modify their behavior when failures occur frequently. We discuss the use of past experience to improve the agent's behavior. More precisely, we use past experience to improve the context conditions of the plans contained in the plan library, initially set by a BDI programmer. First, we consider a deterministic and fully observable environment and we discuss how to modify the BDI agent to prevent re-occurrence of failures, which is not a trivial task. Then, we discuss how we can use decision trees to improve the agent's behavior in a non-deterministic environment.