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H. Francis Song

3 accepted papers

2021

Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents

NeurIPS 2021poster

There has been rapidly growing interest in meta-learning as a method for increasing the flexibility and sample efficiency of reinforcement learning. One problem in this area of research, however, has been a scarcity of adequate benchmark tasks. In general, the structure underlying past benchmarks ha…

Cited by 38SourcecodeScholar
2020

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

ICLR 2020poster

Some of the most successful applications of deep reinforcement learning to challenging domains in discrete and continuous control have used policy gradient methods in the on-policy setting. However, policy gradients can suffer from large variance that may limit performance, and in practice require c…

Cited by 136SourceScholar
2019

Relational Forward Models for Multi-Agent Learning

ICLR 2019poster

The behavioral dynamics of multi-agent systems have a rich and orderly structure, which can be leveraged to understand these systems, and to improve how artificial agents learn to operate in them. Here we introduce Relational Forward Models (RFM) for multi-agent learning, networks that can learn to…

Cited by 95SourcePDFScholar