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06/16/2023
Dynamic Size Message Scheduling for Multi-Agent Communication under Limited Bandwidth
Communication plays a vital role in multi-agent systems, fostering colla...
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05/09/2023
Distributional Multi-Objective Decision Making
For effective decision support in scenarios with conflicting objectives,...
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05/02/2023
Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making
Experts advising decision-makers are likely to display expertise which v...
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04/18/2023
Safe reinforcement learning with self-improving hard constraints for multi-energy management systems
Safe reinforcement learning (RL) with hard constraint guarantees is a pr...
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03/22/2023
Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees
Although deep reinforcement learning (DRL) has many success stories, the...
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03/06/2023
The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
Partially Observable Markov Decision Processes (POMDPs) are useful tools...
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01/30/2023
Evaluating COVID-19 vaccine allocation policies using Bayesian m-top exploration
Individual-based epidemiological models support the study of fine-graine...
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01/30/2023
Transferring Multiple Policies to Hotstart Reinforcement Learning in an Air Compressor Management Problem
Many instances of similar or almost-identical industrial machines or too...
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01/18/2023
Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization
Multi-objective reinforcement learning (MORL) algorithms tackle sequenti...
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01/13/2023
Bridging the Gap Between Single and Multi Objective Games
A classic model to study strategic decision making in multi-agent system...
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07/08/2022
Safe reinforcement learning for multi-energy management systems with known constraint functions
Reinforcement learning (RL) is a promising optimal control technique for...
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04/11/2022
Pareto Conditioned Networks
In multi-objective optimization, learning all the policies that reach Pa...
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04/11/2022
Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning
Infectious disease outbreaks can have a disruptive impact on public heal...
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12/23/2021
Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) enables us to create adaptive ...
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12/17/2021
Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes (Technical Report)
We consider the challenge of policy simplification and verification in t...
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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...
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11/17/2021
Preference Communication in Multi-Objective Normal-Form Games
We study the problem of multiple agents learning concurrently in a multi...
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06/25/2021
Dealing with Expert Bias in Collective Decision-Making
Quite some real-world problems can be formulated as decision-making prob...
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06/10/2021
Synthesising Reinforcement Learning Policies through Set-Valued Inductive Rule Learning
Today's advanced Reinforcement Learning algorithms produce black-box pol...
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04/20/2021
Model-predictive control and reinforcement learning in multi-energy system case studies
Model-predictive-control (MPC) offers an optimal control technique to es...
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03/17/2021
A Practical Guide to Multi-Objective Reinforcement Learning and Planning
Real-world decision-making tasks are generally complex, requiring trade-...
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11/14/2020
Opponent Learning Awareness and Modelling in Multi-Objective Normal Form Games
Many real-world multi-agent interactions consider multiple distinct crit...
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03/30/2020
Deep reinforcement learning for large-scale epidemic control
Epidemics of infectious diseases are an important threat to public healt...
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01/26/2020
An interpretable semi-supervised classifier using two different strategies for amended self-labeling
In the context of some machine learning applications, obtaining data ins...
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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...
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01/15/2020
Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping
We present a new model-based reinforcement learning algorithm, Cooperati...
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11/22/2019
Fleet Control using Coregionalized Gaussian Process Policy Iteration
In many settings, as for example wind farms, multiple machines are insta...
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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...
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11/22/2019
Thompson Sampling for Factored Multi-Agent Bandits
Multi-agent coordination is prevalent in many real-world applications. H...
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09/30/2019
IPC-Net: 3D point-cloud segmentation using deep inter-point convolutional layers
Over the last decade, the demand for better segmentation and classificat...
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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...
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07/18/2019
Transfer Learning Across Simulated Robots With Different Sensors
For a robot to learn a good policy, it often requires expensive equipmen...
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03/11/2019
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics
Value-based reinforcement-learning algorithms are currently state-of-the...
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02/07/2019
The Actor-Advisor: Policy Gradient With Off-Policy Advice
Actor-critic algorithms learn an explicit policy (actor), and an accompa...
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09/20/2018
Dynamic Weights in Multi-Objective Deep Reinforcement Learning
Many real-world decision problems are characterized by multiple objectiv...
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08/13/2018
Directed Policy Gradient for Safe Reinforcement Learning with Human Advice
Many currently deployed Reinforcement Learning agents work in an environ...
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02/21/2018
Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making
In multi-objective decision planning and learning, much attention is pai...
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11/16/2017
Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies
Pandemic influenza has the epidemic potential to kill millions of people...
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11/10/2017
Learning with Options that Terminate Off-Policy
A temporally abstract action, or an option, is specified by a policy and...
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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...
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02/28/2017
Analysing Congestion Problems in Multi-agent Reinforcement Learning
Congestion problems are omnipresent in today's complex networks and repr...
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12/16/2015
Solving stable matching problems using answer set programming
Since the introduction of the stable marriage problem (SMP) by Gale and ...
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02/11/2015
Off-Policy Reward Shaping with Ensembles
Potential-based reward shaping (PBRS) is an effective and popular techni...
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05/21/2014
Off-Policy Shaping Ensembles in Reinforcement Learning
Recent advances of gradient temporal-difference methods allow to learn o...
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02/28/2013
