4 papers
Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank
Wenhao Zhan, Scott Fujimoto, Zheqing Zhu +3
We study the problem of learning an approximate equilibrium in the offline multi-agent reinforcement learning (MARL) setting. We introduce a structural assumption -- the interactio…
Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs
Lili Wu, Ben Evans, Riashat Islam +3
Discovering an informative, or agent-centric, state representation that encodes only the relevant information while discarding the irrelevant is a key challenge towards scaling rei…
The Bias of Harmful Label Associations in Vision-Language Models
Caner Hazirbas, Alicia Sun, Yonathan Efroni +1
Despite the remarkable performance of foundation vision-language models, the shared representation space for text and vision can also encode harmful label associations detrimental…
Prospective Side Information for Latent MDPs
Jeongyeol Kwon, Yonathan Efroni, Shie Mannor +1
In many interactive decision-making settings, there is latent and unobserved information that remains fixed. Consider, for example, a dialogue system, where complete information ab…