Diederik M. Roijers

research

∙ 12/23/2021

Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning

Multi-agent reinforcement learning (MARL) enables us to create adaptive ...

Raphaël Avalos, et al. ∙

research

∙ 12/13/2021

On Nash Equilibria in Normal-Form Games With Vectorial Payoffs

We provide an in-depth study of Nash equilibria in multi-objective norma...

Willem Röpke, et al. ∙

research

∙ 11/17/2021

Preference Communication in Multi-Objective Normal-Form Games

We study the problem of multiple agents learning concurrently in a multi...

Willem Röpke, et al. ∙

research

∙ 06/02/2021

Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making

In many real-world scenarios, the utility of a user is derived from the ...

Conor F. Hayes, et al. ∙

research

∙ 03/17/2021

A Practical Guide to Multi-Objective Reinforcement Learning and Planning

Real-world decision-making tasks are generally complex, requiring trade-...

Conor F. Hayes, et al. ∙

research

∙ 02/01/2021

Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search

In many risk-aware and multi-objective reinforcement learning settings, ...

Conor F. Hayes, et al. ∙

research

∙ 01/19/2021

Scalable Optimization for Wind Farm Control using Coordination Graphs

Wind farms are a crucial driver toward the generation of ecological and ...

Timothy Verstraeten, et al. ∙

research

∙ 11/14/2020

Opponent Learning Awareness and Modelling in Multi-Objective Normal Form Games

Many real-world multi-agent interactions consider multiple distinct crit...

Roxana Rădulescu, et al. ∙

research

∙ 05/04/2020

Time Efficiency in Optimization with a Bayesian-Evolutionary Algorithm

Not all generate-and-test search algorithms are created equal. Bayesian ...

Gongjin Lan, et al. ∙

research

∙ 01/21/2020

Learning Directed Locomotion in Modular Robots with Evolvable Morphologies

We generalize the well-studied problem of gait learning in modular robot...

Gongjin Lan, et al. ∙

research

∙ 01/17/2020

A utility-based analysis of equilibria in multi-objective normal form games

In multi-objective multi-agent systems (MOMAS), agents explicitly consid...

Roxana Rădulescu, et al. ∙

research

∙ 01/15/2020

Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping

We present a new model-based reinforcement learning algorithm, Cooperati...

Eugenio Bargiacchi, et al. ∙

research

∙ 11/22/2019

Multi-Agent Thompson Sampling for Bandit Applications with Sparse Neighbourhood Structures

Multi-agent coordination is prevalent in many real-world applications. H...

Timothy Verstraeten, et al. ∙

research

∙ 11/22/2019

Thompson Sampling for Factored Multi-Agent Bandits

Multi-agent coordination is prevalent in many real-world applications. H...

Timothy Verstraeten, et al. ∙

research

∙ 09/06/2019

Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey

The majority of multi-agent system (MAS) implementations aim to optimise...

Roxana Rădulescu, et al. ∙

research

∙ 03/11/2019

Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics

Value-based reinforcement-learning algorithms are currently state-of-the...

Denis Steckelmacher, et al. ∙

research

∙ 02/07/2019

The Actor-Advisor: Policy Gradient With Off-Policy Advice

Actor-critic algorithms learn an explicit policy (actor), and an accompa...

Hélène Plisnier, et al. ∙

research

∙ 09/20/2018

Dynamic Weights in Multi-Objective Deep Reinforcement Learning

Many real-world decision problems are characterized by multiple objectiv...

Axel Abels, et al. ∙

research

∙ 08/13/2018

Directed Policy Gradient for Safe Reinforcement Learning with Human Advice

Many currently deployed Reinforcement Learning agents work in an environ...

Hélène Plisnier, et al. ∙

research

∙ 02/21/2018

Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making

In multi-objective decision planning and learning, much attention is pai...

Luisa M Zintgraf, et al. ∙

research

∙ 11/16/2017

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies

Pandemic influenza has the epidemic potential to kill millions of people...

Pieter Libin, et al. ∙

research

∙ 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...

Denis Steckelmacher, et al. ∙

research

∙ 10/09/2016

Multi-Objective Deep Reinforcement Learning

We propose Deep Optimistic Linear Support Learning (DOL) to solve high-d...

Hossam Mossalam, et al. ∙

research

∙ 06/22/2016

Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information

Zero-sum stochastic games provide a rich model for competitive decision ...

Auke J. Wiggers, et al. ∙

research

∙ 11/29/2015

Solving Transition-Independent Multi-agent MDPs with Sparse Interactions (Extended version)

In cooperative multi-agent sequential decision making under uncertainty,...

Joris Scharpff, et al. ∙

Diederik M. Roijers

Featured Co-authors

Shimon Whiteson

Jakub M. Tomczak

Marcello Restelli

Ann Nowé

Frans A. Oliehoek

Catholijn M. Jonker

A. E. Eiben

Richard Dazeley

Philippe Lemey

Peter Vrancx

Anna Harutyunyan

Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning

On Nash Equilibria in Normal-Form Games With Vectorial Payoffs

Preference Communication in Multi-Objective Normal-Form Games

Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making

A Practical Guide to Multi-Objective Reinforcement Learning and Planning

Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search

Scalable Optimization for Wind Farm Control using Coordination Graphs

Opponent Learning Awareness and Modelling in Multi-Objective Normal Form Games

Time Efficiency in Optimization with a Bayesian-Evolutionary Algorithm

Learning Directed Locomotion in Modular Robots with Evolvable Morphologies

A utility-based analysis of equilibria in multi-objective normal form games

Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping

Multi-Agent Thompson Sampling for Bandit Applications with Sparse Neighbourhood Structures

Thompson Sampling for Factored Multi-Agent Bandits

Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey

Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics

The Actor-Advisor: Policy Gradient With Off-Policy Advice

Dynamic Weights in Multi-Objective Deep Reinforcement Learning

Directed Policy Gradient for Safe Reinforcement Learning with Human Advice

Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies

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

Multi-Objective Deep Reinforcement Learning

Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information

Solving Transition-Independent Multi-agent MDPs with Sparse Interactions (Extended version)