
Revisiting Fundamentals of Experience Replay
Experience replay is central to offpolicy algorithms in deep reinforcem...
read it

Deep Reinforcement Learning and its Neuroscientific Implications
The emergence of powerful artificial intelligence is defining new resear...
read it

Adapting Behaviour for Learning Progress
Determining what experience to generate to best facilitate learning (i.e...
read it

Hindsight Credit Assignment
We consider the problem of efficient credit assignment in reinforcement ...
read it

Conditional Importance Sampling for OffPolicy Learning
The principal contribution of this paper is a conceptual framework for o...
read it

Adaptive TradeOffs in OffPolicy Learning
A great variety of offpolicy learning algorithms exist in the literatur...
read it

Fast Task Inference with Variational Intrinsic Successor Features
It has been established that diverse behaviors spanning the controllable...
read it

The Termination Critic
In this work, we consider the problem of autonomously discovering behavi...
read it

Statistics and Samples in Distributional Reinforcement Learning
We present a unifying framework for designing and analysing distribution...
read it

A Geometric Perspective on Optimal Representations for Reinforcement Learning
This paper proposes a new approach to representation learning based on g...
read it

Autoregressive Quantile Networks for Generative Modeling
We introduce autoregressive implicit quantile networks (AIQN), a fundame...
read it

Implicit Quantile Networks for Distributional Reinforcement Learning
In this work, we build on recent advances in distributional reinforcemen...
read it

Lowpass Recurrent Neural Networks  A memory architecture for longerterm correlation discovery
Reinforcement learning (RL) agents performing complex tasks must be able...
read it

Distributed Distributional Deterministic Policy Gradients
This work adopts the very successful distributional perspective on reinf...
read it

An Analysis of Categorical Distributional Reinforcement Learning
Distributional approaches to valuebased reinforcement learning model th...
read it

Distributional Reinforcement Learning with Quantile Regression
In reinforcement learning an agent interacts with the environment by tak...
read it

Rainbow: Combining Improvements in Deep Reinforcement Learning
The deep reinforcement learning community has made several independent i...
read it

A Distributional Perspective on Reinforcement Learning
In this paper we argue for the fundamental importance of the value distr...
read it

The Cramer Distance as a Solution to Biased Wasserstein Gradients
The Wasserstein probability metric has received much attention from the ...
read it
Will Dabney
is this you? claim profile