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Temporal Representations for Exploration: Learning Complex Exploratory Behavior without Extrinsic Rewards
Faisal Mohamed, Catherine Ji, Benjamin Eysenbach +1
Effective exploration in reinforcement learning requires not only tracking where an agent has been, but also understanding how the agent perceives and represents the world. To lear…
Low-N Protein Activity Optimization with FolDE
Jacob B. Roberts, Catherine R. Ji, Isaac Donnell +13
Proteins are traditionally optimized through the costly construction and measurement of many mutants. Active Learning-assisted Directed Evolution (ALDE) alleviates that cost by pre…
Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration
Chirayu Nimonkar, Shlok Shah, Catherine Ji +1
For groups of autonomous agents to achieve a particular goal, they must engage in coordination and long-horizon reasoning. Rather than relying on complex reward functions and expli…
Horizon Generalization in Reinforcement Learning
Vivek Myers, Catherine Ji, Benjamin Eysenbach
We study goal-conditioned RL through the lens of generalization, but not in the traditional sense of random augmentations and domain randomization. Rather, we aim to learn goal-dir…