Model-based reinforcement learning has drawn considerable interest in re...
While deep reinforcement learning has shown important empirical success,...
Go-Explore achieved breakthrough performance on challenging reinforcemen...
Non-parametric episodic memory can be used to quickly latch onto high-re...
Go-Explore achieved breakthrough performance on challenging reinforcemen...
Hierarchical Reinforcement Learning (HRL) has held longstanding promise ...
MuZero, a model-based reinforcement learning algorithm that uses a value...
Sequential decision making, commonly formalized as Markov Decision Proce...
Sequential decision making, commonly formalized as Markov Decision Proce...
Monte Carlo Tree Search (MCTS) efficiently balances exploration and
expl...
Planning and reinforcement learning are two key approaches to sequential...
This paper studies the potential of the return distribution for explorat...
A core novelty of Alpha Zero is the interleaving of tree search and deep...
We present an extension of Monte Carlo Tree Search (MCTS) that strongly
...
This paper studies directed exploration for reinforcement learning agent...
This article provides the first survey of computational models of emotio...
In this paper we study how to learn stochastic, multimodal transition
dy...