6 citations · 9 across the 5 of their papers we have counts for
3 papers · 1 filter
Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability
Taewoon Kim, Vincent François-Lavet, Michael Cochez
Reinforcement learning under partial observability requires deciding what information to retain, yet most memory-based approaches do not explicitly model short-term-to-long-term tr…
Hadamard Representation: Scaffolding Performance Across Model-free RL
Jacob E. Kooi, Zhao Yang, Mark Hoogendoorn +1
Deep reinforcement learning agents progressively lose representational capacity during training: neurons become dormant, removing active capacity from the network, and effective ra…
Domain Adversarial Reinforcement Learning
Bonnie Li, Vincent François-Lavet, Thang Doan +1
We consider the problem of generalization in reinforcement learning where visual aspects of the observations might differ, e.g. when there are different backgrounds or change in co…