Proceedings of the first international conference on Principles of knowledge representation and reasoning
C4.5: programs for machine learning
C4.5: programs for machine learning
Toward robust agent control in open environments
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Machine Learning
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Neuro-Dynamic Programming
The control of reasoning in resource-bounded agents
The Knowledge Engineering Review
Meta-Level Reasoning in Deliberative Agents
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Managing online self-adaptation in real-time environments
IWSAS'01 Proceedings of the 2nd international conference on Self-adaptive software: applications
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Agents operating in open environments must be able to adapt their processing to available resources, deadlines, their goal criteria, and their current problem solving contexts. This paper describes the role of meta-cognition in this process; in particular, we define a meta-cognition framework that uses Naive Bayesian classification of the agent's current context in order to represent the meta-level control problem as a Markov Decision Process.