One of the key behavioral characteristics used in neuroscience to determ...
Learning to control an agent from data collected offline in a rich
pixel...
Humans commonly solve complex problems by decomposing them into easier
s...
In recent years, a growing number of deep model-based reinforcement lear...
Humans have the capability, aided by the expressive compositionality of ...
We propose the k-Shortest-Path (k-SP) constraint: a novel constraint on ...
We investigate the discounting mismatch in actor-critic algorithm
implem...
Deep model-based Reinforcement Learning (RL) has the potential to
substa...
In an effort to better understand the different ways in which the discou...
While recent progress has spawned very powerful machine learning systems...
We consider tackling a single-agent RL problem by distributing it to n
l...
In this paper, we propose a framework for solving a single-agent task by...
The temporal-difference methods TD(λ) and Sarsa(λ) form a
core part of m...
The true online TD(λ) algorithm has recently been proposed (van
Seijen a...
Efficient planning plays a crucial role in model-based reinforcement
lea...