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Many problem-solving tasks can be formalized as constraint saris/action problems (CSP). In a multi-agent setting, information about constraints and variables may be distributed among different agents and kept confidential. Existing algorithms for distributed constraint satisfaction consider mainly the case where access to variables is restricted to certain agents, but information about constraints can be exchanged among them. In this paper, we propose methods where constraints are private but variables can be manipulated by any agent. We describe a new algorithm for distributed CSPs, called asynchronous aggregation search (AAS). It differs from existing methods in that it treats simultaneously sets of partial solutions and it exchanges information about aggregated valuations for combinations of variables. While the approach we propose provides a more general framework for dealing with privacy requirements, its overall performance is comparable or better than that of existing methods, as shown by the experiments.

Distributed asynchronous search with private constraints (extended abstract)