Technical Note: \cal Q-Learning
Machine Learning
Relational reinforcement learning
Machine Learning - Special issue on inducive logic programming
An Integrated Approach of Learning, Planning, and Execution
Journal of Intelligent and Robotic Systems
Efficient Exploration In Reinforcement Learning
Efficient Exploration In Reinforcement Learning
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
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Classical planning domain representations assume all the objects from one type are exactly the same. But when solving problems in the real world systems, the execution of a plan that theoretically solves a problem, can fail because of not properly capturing the special features of an object in the initial representation. We propose to capture this uncertainty about the world with an architecture that integrates planning, execution and learning. In this paper, we describe the PELA system (Planning-Execution-Learning Architecture). This system generates plans, executes those plans in the real world, and automatically acquires knowledge about the behaviour of the objects to strengthen the execution processes in the future.