TY - CHAP
T1 - Bargaining through amalgamation
AU - Zhang, Dongmo
AU - Plaza, Enric
PY - 2025
Y1 - 2025
N2 - This paper presents a bargaining framework grounded in the methods of conceptual blending and amalgamation to support automated negotiation. The bargaining scenario is represented using a content-rich and descriptive formal language, featuring a subsumption hierarchy among negotiation terms. Bargainers generate proposals or counter-proposals within the amalgam of their initial offers, incorporating unifications of all possible generalizations of these offers. Under this framework, we prove that any bargaining sequence converges to an agreement when each bargainer makes minimal concessions according to their individual preferences. The resulting agreement satisfies individual rationality, collective rationality, Pareto optimality, and contract independence. Furthermore, we show that this solution is uniquely characterized by these properties.
AB - This paper presents a bargaining framework grounded in the methods of conceptual blending and amalgamation to support automated negotiation. The bargaining scenario is represented using a content-rich and descriptive formal language, featuring a subsumption hierarchy among negotiation terms. Bargainers generate proposals or counter-proposals within the amalgam of their initial offers, incorporating unifications of all possible generalizations of these offers. Under this framework, we prove that any bargaining sequence converges to an agreement when each bargainer makes minimal concessions according to their individual preferences. The resulting agreement satisfies individual rationality, collective rationality, Pareto optimality, and contract independence. Furthermore, we show that this solution is uniquely characterized by these properties.
KW - amalgamation
KW - automated negotiation
KW - bargaining
KW - feature logic
UR - https://www.scopus.com/pages/publications/85210159518
UR - https://go.openathens.net/redirector/westernsydney.edu.au?url=https://doi.org/10.1007/978-3-031-77367-9_3
U2 - 10.1007/978-3-031-77367-9_3
DO - 10.1007/978-3-031-77367-9_3
M3 - Chapter
AN - SCOPUS:85210159518
SN - 9783031773662
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 25
EP - 41
BT - PRIMA 2024: Principles and Practice of Multi-Agent Systems, 25th International Conference, Kyoto, Japan, November 18-24, 2024, Proceedings
A2 - Arisaka, Ryuta
A2 - Sanchez-Anguix, Victor
A2 - Stein, Sebastian
A2 - Aydoğan, Reyhan
A2 - van der Torre, Leon
A2 - Ito, Takayuki
PB - Springer
CY - Switzerland
ER -