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Robust Reinforcement Learning In Motion Planning, Satinder P. Singh, Andrew G. Barto, Roderic Grupen, Christopher Connolly
Robust Reinforcement Learning In Motion Planning, Satinder P. Singh, Andrew G. Barto, Roderic Grupen, Christopher Connolly
Roderic Grupen
While exploring to find better solutions, an agent performing on-line reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, or even catastrophic, results, often modeled in terms of reaching 'failure' states of the agent's environment. This paper presents a method that uses domain knowledge to reduce the number of failures during exploration. This method formulates the set of actions from which the RL agent composes a control policy to ensure that exploration is conducted in a policy space that excludes most of the unacceptable policies. The resulting action set has a more abstract …
Purification And Characterization Of Porin From Corn (Zea Mays L.) Mitochondria, Philadelphia University
Purification And Characterization Of Porin From Corn (Zea Mays L.) Mitochondria, Philadelphia University
Philadelphia University, Jordan
No abstract provided.