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20142026
most citedA Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity

192 citations · 199 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.MA2026

[COMP25] The Automated Negotiating Agents Competition (ANAC) 2025 Challenges and Results

Reyhan Aydoğan, Tim Baarslag, Tamara C. P. Florijn +3

This paper presents the primary research challenges and key findings from the 15th International Automated Negotiating Agents Competition (ANAC 2025), one of the official competiti…

cs.MA2018★ 2 cited

Energy Contract Settlements through Automated Negotiation in Residential Cooperatives

Shantanu Chakraborty, Tim Baarslag, Michael Kaisers

This paper presents an automated peer-to-peer (P2P) negotiation strategy for settling energy contracts among prosumers in a Residential Energy Cooperative (REC) considering heterog…

cs.MA2018★ 1 cited

An Optimal Rewiring Strategy for Reinforcement Social Learning in Cooperative Multiagent Systems

Hongyao Tang, Li Wang, Zan Wang +2

Multiagent coordination in cooperative multiagent systems (MASs) has been widely studied in both fixed-agent repeated interaction setting and the static social learning framework.…

cs.MA2017★ 192 cited

A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity

Pablo Hernandez-Leal, Michael Kaisers, Tim Baarslag +1

The key challenge in multiagent learning is learning a best response to the behaviour of other agents, which may be non-stationary: if the other agents adapt their strategy as well…

cs.MA2016

Can we reach Pareto optimal outcomes using bottom-up approaches?

Victor Sanchez-Anguix, Reyhan Aydogan, Tim Baarslag +1

Traditionally, researchers in decision making have focused on attempting to reach Pareto Optimality using horizontal approaches, where optimality is calculated taking into account…