1 citations · 2 across the 4 of their papers we have counts for
4 papers
MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning
Florian Felten, Umut Ucak, Hicham Azmani +10
Many challenging tasks such as managing traffic systems, electricity grids, or supply chains involve complex decision-making processes that must balance multiple conflicting object…
BRExIt: On Opponent Modelling in Expert Iteration
Daniel Hernandez, Hendrik Baier, Michael Kaisers
Finding a best response policy is a central objective in game theory and multi-agent learning, with modern population-based training approaches employing reinforcement learning alg…
Online Planning in POMDPs with Self-Improving Simulators
Jinke He, Miguel Suau, Hendrik Baier +2
How can we plan efficiently in a large and complex environment when the time budget is limited? Given the original simulator of the environment, which may be computationally very d…
The Text-Based Adventure AI Competition
Timothy Atkinson, Hendrik Baier, Tara Copplestone +2
In 2016, 2017, and 2018 at the IEEE Conference on Computational Intelligence in Games, the authors of this paper ran a competition for agents that can play classic text-based adven…