Anytime coalition structure generation: an average case study
Proceedings of the third annual conference on Autonomous Agents
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
Sequencing of Contract Types for Anytime Task Reallocation
AMET '98 Selected Papers from the First International Workshop on Agent Mediated Electronic Trading on Agent Mediated Electronic Commerce
Equilibrium analysis of the possibilities of unenforced exchange in multiagent systems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Advantages of a leveled commitment contracting protocol
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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In automated negotiation systems consisting of self-interested agents, contracts have traditionally been binding. Such contracts do not allow agents to efficiently accommodate future events. Game theory has proposed contingency contracts to solve this problem. Among computational agents, contingency contracts are often impractical due to large numbers of interdependent and unanticipated future events to be conditioned on, and because some events are not mutually observable. This paper proposes a leveled commitment contracting protocol that allows self-interested agents to efficiently accommodate future events by having the possibility of unilaterally decommitting from a contract based on local reasoning. A decommitment penalty is assigned to both agents in a contract: to be freed from the obligations of the contract, an agent only pays this penalty to the other party. It is shown through formal analysis of multiple contracting settings that this leveled commitment feature in a contracting protocol increases Pareto efficiency of deals and can make contracts individually rational when no full commitment contract can. This advantage holds even if the agents decommit manipulatively.