5 citations · 5 across the 5 of their papers we have counts for
5 papers
Certifying cooperation: a novel approach to cooperative multi-agent task generation
Yannick Molinghen, Hugo Charels, Tom Lenaerts
A shared reward gives agents a common objective, but leaves open when, how and even whether they must cooperate to succeed. We address these questions in the Laser Learning Environ…
Reinforcement Learning Methods for Neighborhood Selection in Local Search
Yannick Molinghen, Augustin Delecluse, Renaud De Landtsheer +1
Reinforcement learning has recently gained traction as a means to improve combinatorial optimization methods, yet its effectiveness within local search metaheuristics specifically…
Zero-Incentive Dynamics: a look at reward sparsity through the lens of unrewarded subgoals
Yannick Molinghen, Tom Lenaerts
This work re-examines the commonly held assumption that the frequency of rewards is a reliable measure of task difficulty in reinforcement learning. We identify and formalize a str…
FRAUD-RLA: A new reinforcement learning adversarial attack against credit card fraud detection
Daniele Lunghi, Yannick Molinghen, Alkis Simitsis +2
Adversarial attacks pose a significant threat to data-driven systems, and researchers have spent considerable resources studying them. Despite its economic relevance, this trend la…
Laser Learning Environment: A new environment for coordination-critical multi-agent tasks
Yannick Molinghen, Raphaël Avalos, Mark Van Achter +2
We introduce the Laser Learning Environment (LLE), a collaborative multi-agent reinforcement learning environment in which coordination is central. In LLE, agents depend on each ot…