Centralized versus decentralized computing: organizational considerations and management options
ACM Computing Surveys (CSUR)
Rules of encounter: designing conventions for automated negotiation among computers
Rules of encounter: designing conventions for automated negotiation among computers
Collaborative assignment: a multiagent negotiation approach using BDI concepts
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
An asynchronous complete method for distributed constraint optimization
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Solving Distributed Constraint Optimization Problems Using Cooperative Mediation
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Task allocation via coalition formation among autonomous agents
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Evaluating multi-agent system architectures: a case study concerning dynamic resource allocation
ESAW'02 Proceedings of the 3rd international conference on Engineering societies in the agents world III
Information Sciences: an International Journal
Performance of multiagent taxi dispatch on extended-runtime taxi availability: a simulation study
IEEE Transactions on Intelligent Transportation Systems
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The collaborative linear assignment problem (CLAP) is a recent framework being developed to provide an intellectual basis for investigating uncluttered agent-based solutions for a fundamental class of combinatorial assignment (or allocation) applications. One key motivation of the research on CLAP is the hope that it can shed new light on adopting agent approaches for solving traditional combinatorial problems in general. To accommodate the various levels of control on agent sociability, typically different application-specific solutions to CLAP are required. In this paper, we take an architectural perspective, classifying solutions according to three typical control structures, namely, centralized, distributed, and decentralized. Existing work focuses mainly on centralized and distributed systems. In this paper, based on the Multi-Agent Assignment Algorithm ({\rm MA}^{3}) used for distributed systems, we propose a new mechanism for a totally decentralized architecture. This proposed mechanism incorporates a novel idea called collaborative Local Mediation (LM), therefore, we term this mechanism {\rm MA}^{3}{\hbox{-}}{\rm{LM}}. We prove that the decentralized {\rm MA}^{3}{\hbox{-}}{\rm{LM}} does not increase the worst-case reasoning complexity when compared to its partially decentralized counterpart. An example illustrates the new mechanism, with emphasis on how it performs collaborative local mediation.