Abstract (EN)

Multiagent resource allocation is a timely and exciting area of research at the interface of Computer Science and Eco- nomics. One of the main challenges in this area is the high complexity of negotiation. In particular, the complexity of the task of identifying rational deals, i.e. deals that are bene- ficial for all participants, often hinders the successful transfer of theoretical results to practical applications. To address this issue, we propose several protocols designed to tame the complexity of negotiation by exploiting structural properties of the utility functions used by agents to model their pref- erences over alternative bundles of resources. In particular, we consider domains where utility functions are k-additive (that is, synergies between different resources are restricted to bundles of at most k items) and tree-structured in the sense that the bundles for which there are synergies do not overlap. We show how protocols exploiting these properties can allow for drastically simplified negotiation processes.