7 citations · 13 across the 4 of their papers we have counts for
4 papers · 1 filter
Measuring and Mitigating Interference in Reinforcement Learning
Vincent Liu, Han Wang, Ruo Yu Tao +3
Catastrophic interference is common in many network-based learning systems, and many proposals exist for mitigating it. Before overcoming interference we must understand it better.…
Agent-State Construction with Auxiliary Inputs
Ruo Yu Tao, Adam White, Marlos C. Machado
In many, if not every realistic sequential decision-making task, the decision-making agent is not able to model the full complexity of the world. The environment is often much larg…
Novelty Search in Representational Space for Sample Efficient Exploration
Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau
We present a new approach for efficient exploration which leverages a low-dimensional encoding of the environment learned with a combination of model-based and model-free objective…
Towards Solving Text-based Games by Producing Adaptive Action Spaces
Ruo Yu Tao, Marc-Alexandre Côté, Xingdi Yuan +1
To solve a text-based game, an agent needs to formulate valid text commands for a given context and find the ones that lead to success. Recent attempts at solving text-based games…