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Combinatorial auctions, that is, auctions where bidders can bid on combinations of items, tend to lead to more efficient allocations than traditional auction mechanisms in multi-item auctions where the agents' valuations of the items are not additive. However, determining the winners so as to maximize revenue is N P-complete. First, we analyze existing(More)
Coalition formation is a key topic in multiagent systems. One may prefer a coalition structure that maximizes the sum of the values of the coalitions, but often the number of coalition structures is too large to allow exhaustive search for the optimal one. Furthermore, nding the optimal coalition structure is NP-complete. But then, can the coalition(More)
In multiagent settings where the agents have different preferences, preference aggregation is a central issue. Voting is a general method for preference aggregation, but seminal results have shown that all general voting protocols are manipulable. One could try to avoid manipulation by using protocols where determining a beneficial manipulation is hard.(More)
Two minimal requirements for a satisfactory multiagent learning algorithm are that it 1. learns to play optimally against stationary opponents and 2. converges to a Nash equilibrium in self-play. The previous algorithm that has come closest, WoLF-IGA, has been proven to have these two properties in 2-player 2-action (repeated) games—assuming that the(More)
Automated negotiation systems with self-interested agents are becoming increasingly important. One reason for this is the technology push of a growing standardized which separately designed agents belonging to diierent organizations can int e r a c t i n a n o p e n e n vironment in real-time and safely carry out transactions. The second reason is strong(More)
This paper presents a formalization of the bidding and awarding decision process that was left undefined in the original contract net task allocation protocol. This formalization is based on marginal cost calculations based on local agent criteria. In this way, agents having very different local criteria (based on their self-interest) can interact to(More)
Combinatorial auctions where bidders can bid on bundles of items can lead to more economical allocations, but determining the winners is NP-complete and inapproximable. We present CABOB, a sophisticated search algorithm for the problem. It uses decomposition techniques, upper and lower bounding (also across components), elaborate and dynamically chosen bid(More)