Searching for "Learning to Take Actions." – sorted by Relevance.
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Learning to Take Actions
- Learning to Take Actions Roni Khardon y Department of Computer Science University of Edinburgh
- Cited by 36 (7 self) – Add To MetaCart
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Skill acquisition via transfer learning and advice taking
- by a finite number of features, and the agent takes actions to cause the state to change. In Q-learning
- Cited by 8 (1 self) – Add To MetaCart
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Adaptive Intelligent Mobile Robots
- . The most naive, and easiest, strategy is to learn to take the action, on each step, that maximizes
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Wireless Sensor Networks for Commercial Lighting Control: Decision Making with Multi-agent Systems
- or taking the median of their actions. Additionally, confidence values can be used to attenuate the global
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Learning in Order to Reason: The Approach
- -monotonically. Learning to Take Action (Khardon 1996) extends the framework in another direction and studies planning
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Model-Based Learning of Interaction Strategies in Multi-Agent Systems
- ] Roni Khardon. Learning to take actions. In Proceeding of the thirteenth National Conference
- Cited by 15 (4 self) – Add To MetaCart
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Intelligent Control Using a Neuro-Fuzzy Network
- . An intelligent control system should be able to learn and to take action in a way similar to humans. It should
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Practical Reinforcement Learning in Continuous Spaces
- and render the approximation useless. In Q-learning, taking the action a from state s, resulting in a
- Cited by 66 (2 self) – Add To MetaCart
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Practitioners
- , and decisions about action they need to take to make further progress in learning. In order to do this
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W-learning: Competition among selfish Q-learners
- of the actions it takes. By trial-and-error, the agent learns to take the actions which maximise its rewards. 2
- Cited by 9 (4 self) – Add To MetaCart

