10 citations · 54 across the 39 of their papers we have counts for
6 papers · 1 filter
Dynamic Incentivized Cooperation under Changing Rewards
Philipp Altmann, Thomy Phan, Maximilian Zorn +2
Peer incentivization (PI) is a popular multi-agent reinforcement learning approach where all agents can reward or penalize each other to achieve cooperation in social dilemmas. Des…
PIMAEX: Multi-Agent Exploration through Peer Incentivization
Michael Kölle, Johannes Tochtermann, Julian Schönberger +3
While exploration in single-agent reinforcement learning has been studied extensively in recent years, considerably less work has focused on its counterpart in multi-agent reinforc…
Emergence in Multi-Agent Systems: A Safety Perspective
Philipp Altmann, Julian Schönberger, Steffen Illium +5
Emergent effects can arise in multi-agent systems (MAS) where execution is decentralized and reliant on local information. These effects may range from minor deviations in behavior…
MEDIATE: Mutually Endorsed Distributed Incentive Acknowledgment Token Exchange
Philipp Altmann, Katharina Winter, Michael Kölle +3
Recent advances in multi-agent systems (MAS) have shown that incorporating peer incentivization (PI) mechanisms vastly improves cooperation. Especially in social dilemmas, communic…
Learning to Participate through Trading of Reward Shares
Michael Kölle, Tim Matheis, Philipp Altmann +1
Enabling autonomous agents to act cooperatively is an important step to integrate artificial intelligence in our daily lives. While some methods seek to stimulate cooperation by le…
Attention-Based Recurrence for Multi-Agent Reinforcement Learning under Stochastic Partial Observability
Thomy Phan, Fabian Ritz, Philipp Altmann +5
Stochastic partial observability poses a major challenge for decentralized coordination in multi-agent reinforcement learning but is largely neglected in state-of-the-art research…