Self-Supervision for Reinforcement Learning

Ankesh Anand · Bogdan Mazoure · Amy Zhang · Thang Doan · Khurram Javed · R Devon Hjelm · Martha White

Abstract Workshop Website
Fri 7 May, 5:45 a.m. PDT


Reinforcement learning entails letting an agent learn through interaction with an environment. The formalism is powerful in it’s generality, and presents us with a hard open-ended problem: how can we design agents that learn efficiently, and generalize well, given only sensory information and a scalar reward signal? The goal of this workshop is to explore the role of self-supervised learning within reinforcement learning agents, to make progress towards this goal.

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Timezone: America/Los_Angeles »