Web: http://arxiv.org/abs/2201.11783

Jan. 31, 2022, 2:11 a.m. | Ramnath Kumar, Tristan Deleu, Yoshua Bengio

cs.LG updates on arXiv.org arxiv.org

We present a learning mechanism for reinforcement learning of closely related
skills parameterized via a skill embedding space. Our approach is grounded on
the intuition that nothing makes you learn better than a coevolving adversary.
The main contribution of our work is to formulate an adversarial training
regime for reinforcement learning with the help of entropy-regularized policy
gradient formulation. We also adapt existing measures of causal attribution to
draw insights from the skills learned. Our experiments demonstrate that the
adversarial …

arxiv learning networks rl

More from arxiv.org / cs.LG updates on arXiv.org

Director, Data Science (Advocacy & Nonprofit)

@ Civis Analytics | Remote

Data Engineer

@ Rappi | [CO] Bogotá

Data Scientist V, Marketplaces Personalization (Remote)

@ ID.me | United States (U.S.)

Product OPs Data Analyst (Flex/Remote)

@ Scaleway | Paris

Big Data Engineer

@ Risk Focus | Riga, Riga, Latvia

Internship Program: Machine Learning Backend

@ Nextail | Remote job