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Raksha Kumaraswamy

2 accepted papers

2021

Continual Auxiliary Task Learning

NeurIPS 2021poster

Learning auxiliary tasks, such as multiple predictions about the world, can provide many benefits to reinforcement learning systems. A variety of off-policy learning algorithms have been developed to learn such predictions, but as yet there is little work on how to adapt the behavior to gather usefu…

Cited by 10SourcePDFScholar
2018

Context-dependent upper-confidence bounds for directed exploration

NeurIPS 2018poster

Directed exploration strategies for reinforcement learning are critical for learning an optimal policy in a minimal number of interactions with the environment. Many algorithms use optimism to direct exploration, either through visitation estimates or upper confidence bounds, as opposed to data-inef…

Cited by 21SourcePDFScholar