4 citations · 7 across the 2 of their papers we have counts for
4 papers · 1 filter
Pareto Conditioned Networks
Mathieu Reymond, Eugenio Bargiacchi, Ann Nowé
In multi-objective optimization, learning all the policies that reach Pareto-efficient solutions is an expensive process. The set of optimal policies can grow exponentially with th…
Scalable Optimization for Wind Farm Control using Coordination Graphs
Timothy Verstraeten, Pieter-Jan Daems, Eugenio Bargiacchi +3
Wind farms are a crucial driver toward the generation of ecological and renewable energy. Due to their rapid increase in capacity, contemporary wind farms need to adhere to strict…
Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping
Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers +1
We present a new model-based reinforcement learning algorithm, Cooperative Prioritized Sweeping, for efficient learning in multi-agent Markov decision processes. The algorithm allo…
Multi-Agent Thompson Sampling for Bandit Applications with Sparse Neighbourhood Structures
Timothy Verstraeten, Eugenio Bargiacchi, Pieter JK Libin +3
Multi-agent coordination is prevalent in many real-world applications. However, such coordination is challenging due to its combinatorial nature. An important observation in this r…