22 citations · 25 across the 12 of their papers we have counts for
5 papers · 1 filter
Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning
Seijin Kobayashi, Yanick Schimpf, Maximilian Schlegel +12
Large-scale autoregressive models pretrained on next-token prediction and finetuned with reinforcement learning (RL) have achieved unprecedented success on many problem domains. Du…
Embedded Universal Predictive Intelligence: a coherent framework for multi-agent learning
Alexander Meulemans, Rajai Nasser, Maciej Wołczyk +10
The standard theory of model-free reinforcement learning assumes that the environment dynamics are stationary and that agents are decoupled from their environment, such that polici…
MIMIC-MJX: Neuromechanical Emulation of Animal Behavior
Charles Y. Zhang, Yuanjia Yang, Aidan Sirbu +25
The primary output of the nervous system is movement and behavior. While recent advances have democratized pose tracking during complex behavior, kinematic trajectories alone provi…
Sufficient conditions for offline reactivation in recurrent neural networks
Nanda H. Krishna, Colin Bredenberg, Daniel Levenstein +2
During periods of quiescence, such as sleep, neural activity in many brain circuits resembles that observed during periods of task engagement. However, the precise conditions under…
The challenge of hidden gifts in multi-agent reinforcement learning
Dane Malenfant, Blake A. Richards
Sometimes we benefit from actions that others have taken even when we are unaware that they took those actions. For example, if your neighbor chooses not to take a parking spot in…