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    NIPS
    1993
    86views Information Technology» more  NIPS 1993»
    Robust Reinforcement Learning in Motion Planning
    13 years 8 months ago
    Robust Reinforcement Learning in Motion Planning
    Download  www.cs.cmu.edu
    While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
    Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
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    AI
    1999
    Springer
    264views Artificial Intelligence» more  AI 1999»
    Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
    13 years 7 months ago
    Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
    Download  www.mendeley.com
    In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
    Minoru Asada, Eiji Uchibe, Koh Hosoda
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    EWRL
    2008
    186views Machine Learning» more  EWRL 2008»
    Efficient Reinforcement Learning in Parameterized Models: Discrete Parameter Case
    13 years 9 months ago
    Efficient Reinforcement Learning in Parameterized Models: Discrete Parameter Case
    Download  webee.technion.ac.il
    We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
    Kirill Dyagilev, Shie Mannor, Nahum Shimkin
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    JAIR
    2008
    148views more  JAIR 2008»
    Learning Partially Observable Deterministic Action Models
    13 years 7 months ago
    Learning Partially Observable Deterministic Action Models
    Download  www.jair.org
    We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
    Eyal Amir, Allen Chang
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    IJCAI
    2007
    143views Artificial Intelligence» more  IJCAI 2007»
    Direct Code Access in Self-Organizing Neural Networks for Reinforcement Learning
    13 years 9 months ago
    Direct Code Access in Self-Organizing Neural Networks for Reinforcement Learning
    Download  www.aaai.org
    TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD...
    Ah-Hwee Tan
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