Anna Harutyunyan | DeepAI

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∙ 06/16/2023

Bootstrapped Representations in Reinforcement Learning

In reinforcement learning (RL), state representations are key to dealing...

0 Charline Le Lan, et al. ∙

∙ 05/29/2023

DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm

Multi-step learning applies lookahead over multiple time steps and has p...

0 Yunhao Tang, et al. ∙

∙ 01/11/2023

An Analysis of Quantile Temporal-Difference Learning

We analyse quantile temporal-difference learning (QTD), a distributional...

0 Mark Rowland, et al. ∙

∙ 11/01/2021

On the Expressivity of Markov Reward

Reward is the driving force for reinforcement-learning agents. This pape...

15 David Abel, et al. ∙

∙ 11/18/2020

Counterfactual Credit Assignment in Model-Free Reinforcement Learning

Credit assignment in reinforcement learning is the problem of measuring ...

8 Thomas Mesnard, et al. ∙

∙ 11/02/2020

Useful Policy Invariant Shaping from Arbitrary Advice

Reinforcement learning is a powerful learning paradigm in which agents c...

0 Paniz Behboudian, et al. ∙

∙ 12/05/2019

Hindsight Credit Assignment

We consider the problem of efficient credit assignment in reinforcement ...

0 Anna Harutyunyan, et al. ∙

∙ 10/16/2019

Conditional Importance Sampling for Off-Policy Learning

The principal contribution of this paper is a conceptual framework for o...

12 Mark Rowland, et al. ∙

∙ 02/26/2019

The Termination Critic

In this work, we consider the problem of autonomously discovering behavi...

10 Anna Harutyunyan, et al. ∙

∙ 11/10/2017

Learning with Options that Terminate Off-Policy

A temporally abstract action, or an option, is specified by a policy and...

0 Anna Harutyunyan, et al. ∙

∙ 08/22/2017

Reinforcement Learning in POMDPs with Memoryless Options and Option-Observation Initiation Sets

Many real-world reinforcement learning problems have a hierarchical natu...

0 Denis Steckelmacher, et al. ∙

∙ 06/08/2016

Safe and Efficient Off-Policy Reinforcement Learning

In this work, we take a fresh look at some old and new algorithms for of...

0 Remi Munos, et al. ∙

∙ 02/16/2016

Q(λ) with Off-Policy Corrections

We propose and analyze an alternate approach to off-policy multi-step te...

0 Anna Harutyunyan, et al. ∙

∙ 02/11/2015

Off-Policy Reward Shaping with Ensembles

Potential-based reward shaping (PBRS) is an effective and popular techni...

0 Anna Harutyunyan, et al. ∙

∙ 05/21/2014

Off-Policy Shaping Ensembles in Reinforcement Learning

Recent advances of gradient temporal-difference methods allow to learn o...

0 Anna Harutyunyan, et al. ∙

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