6 citations · 18 across the 5 of their papers we have counts for
4 papers · 1 filter
Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning
Fan Feng, Sara Magliacane
In many reinforcement learning tasks, the agent has to learn to interact with many objects of different types and generalize to unseen combinations and numbers of objects. Often a…
A Benchmark and Empirical Analysis for Replay Strategies in Continual Learning
Qihan Yang, Fan Feng, Rosa Chan
With the capacity of continual learning, humans can continuously acquire knowledge throughout their lifespan. However, computational systems are not, in general, capable of learnin…
Factored Adaptation for Non-Stationary Reinforcement Learning
Fan Feng, Biwei Huang, Kun Zhang +1
Dealing with non-stationarity in environments (e.g., in the transition dynamics) and objectives (e.g., in the reward functions) is a challenging problem that is crucial in real-wor…
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning
Biwei Huang, Fan Feng, Chaochao Lu +2
One practical challenge in reinforcement learning (RL) is how to make quick adaptations when faced with new environments. In this paper, we propose a principled framework for adapt…