160 citations · 381 across the 19 of their papers we have counts for
7 papers · 1 filter
Curious Replay for Model-based Adaptation
Isaac Kauvar, Chris Doyle, Linqi Zhou +1
Agents must be able to adapt quickly as an environment changes. We find that existing model-based reinforcement learning agents are unable to do this well, in part because of how t…
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness
Eric Zelikman, Qian Huang, Percy Liang +2
Language model training in distributed settings is limited by the communication cost of gradient exchanges. In this short note, we extend recent work from Malladi et al. (2023), us…
Developmental Curiosity and Social Interaction in Virtual Agents
Chris Doyle, Sarah Shader, Michelle Lau +3
Infants explore their complex physical and social environment in an organized way. To gain insight into what intrinsic motivations may help structure this exploration, we create a…
Interaction Modeling with Multiplex Attention
Fan-Yun Sun, Isaac Kauvar, Ruohan Zhang +4
Modeling multi-agent systems requires understanding how agents interact. Such systems are often difficult to model because they can involve a variety of types of interactions that…
Active World Model Learning with Progress Curiosity
Kuno Kim, Megumi Sano, Julian De Freitas +2
World models are self-supervised predictive models of how the world evolves. Humans learn world models by curiously exploring their environment, in the process acquiring compact ab…
Emergence of Structured Behaviors from Curiosity-Based Intrinsic Motivation
Nick Haber, Damian Mrowca, Li Fei-Fei +1
Infants are experts at playing, with an amazing ability to generate novel structured behaviors in unstructured environments that lack clear extrinsic reward signals. We seek to rep…
Learning to Play with Intrinsically-Motivated Self-Aware Agents
Nick Haber, Damian Mrowca, Li Fei-Fei +1
Infants are experts at playing, with an amazing ability to generate novel structured behaviors in unstructured environments that lack clear extrinsic reward signals. We seek to mat…