265 citations · 1.6k across the 43 of their papers we have counts for
4 papers · 1 filter
Procedural Generalization by Planning with Self-Supervised World Models
Ankesh Anand, Jacob Walker, Yazhe Li +5
One of the key promises of model-based reinforcement learning is the ability to generalize using an internal model of the world to make predictions in novel environments and tasks.…
Muesli: Combining Improvements in Policy Optimization
Matteo Hessel, Ivo Danihelka, Fabio Viola +6
We propose a novel policy update that combines regularized policy optimization with model learning as an auxiliary loss. The update (henceforth Muesli) matches MuZero's state-of-th…
Synthetic Returns for Long-Term Credit Assignment
David Raposo, Sam Ritter, Adam Santoro +5
Since the earliest days of reinforcement learning, the workhorse method for assigning credit to actions over time has been temporal-difference (TD) learning, which propagates credi…
Neural Recursive Belief States in Multi-Agent Reinforcement Learning
Pol Moreno, Edward Hughes, Kevin R. McKee +2
In multi-agent reinforcement learning, the problem of learning to act is particularly difficult because the policies of co-players may be heavily conditioned on information only ob…