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Skip to Search Results- 2Temporal Abstraction
- 1Artificial Intelligence
- 1Computer Games
- 1Model-Based Reinforcement Learning
- 1Monte-carlo tree search
- 1Planning
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Fall 2024
Planning and goal-conditioned reinforcement learning aim to create more efficient and scalable methods for complex, long-horizon tasks. These approaches break tasks into manageable subgoals and leverage prior knowledge to guide learning. However, learned models may predict inaccurate next states...
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Fall 2013
Given nothing but the generative model of the environment, Monte Carlo Tree Search techniques have recently shown spectacular results on domains previously thought to be intractable. In this thesis we try to develop generic techniques for temporal abstraction inside MCTS that would allow the...