TY - GEN
T1 - Comparing Mediated and Unmediated Agent-Based Negotiation in Wi-Fi Channel Assignment
AU - Romero, Marino Tejedor
AU - Murukannaiah, Pradeep Kumar
AU - Gimenez-Guzman, Jose Manuel
AU - Marsa-Maestre, Ivan
AU - Jonker, Catholijn M.
PY - 2023
Y1 - 2023
N2 - Channel allocation in dense Wi-Fi networks is a complex problem due to its nonlinear and exponentially sized solution space. Negotiating over this domain is a challenge, since it is difficult to estimate opponent’s utility. Based on our previous work in mediated techniques, we propose the first two fully-distributed multi-agent negotiations for Wi-Fi channel assignment. Both of them use a simulated annealing sampling process and a noisy model graph estimation. One is designed for Alternating Offers protocols, while the other uses the novel Multiple Offers Protocol for Multilateral Negotiations with Partial Consensus (MOPaC), with experimental promising features for our particular domain. Our experiments compare both proposals against their mediated counterparts, showing similar results on social welfare, Nash product and fairness, but improving privacy and communication overhead.
AB - Channel allocation in dense Wi-Fi networks is a complex problem due to its nonlinear and exponentially sized solution space. Negotiating over this domain is a challenge, since it is difficult to estimate opponent’s utility. Based on our previous work in mediated techniques, we propose the first two fully-distributed multi-agent negotiations for Wi-Fi channel assignment. Both of them use a simulated annealing sampling process and a noisy model graph estimation. One is designed for Alternating Offers protocols, while the other uses the novel Multiple Offers Protocol for Multilateral Negotiations with Partial Consensus (MOPaC), with experimental promising features for our particular domain. Our experiments compare both proposals against their mediated counterparts, showing similar results on social welfare, Nash product and fairness, but improving privacy and communication overhead.
UR - https://www.scopus.com/pages/publications/85142734520
U2 - 10.1007/978-3-031-21203-1_37
DO - 10.1007/978-3-031-21203-1_37
M3 - Conference contribution
SN - 9783031212024
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 592
EP - 601
BT - PRIMA 2022: Principles and Practice of Multi-Agent Systems - 24th International Conference, Proceedings
A2 - Aydoğan, Reyhan
A2 - Criado, Natalia
A2 - Sanchez-Anguix, Victor
A2 - Lang, Jérôme
A2 - Serramia, Marc
PB - Springer Nature Switzerland AG
T2 - 24th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020
Y2 - 16 November 2022 through 18 November 2022
ER -