Distributed Constraint Satisfaction Problems (DCSPs) provide a model to capture a broad range of cooperative multi-agent problem solving settings. Researchers have generally proposed two different sets of approaches for solving DCSPs, backtracking based approaches, such as Asynchronous Backtracking (ABT), and mediation based approaches, such as Asynchronous Partial Overlay (APO). These sets of approaches differ in the levels of coordination employed during conflict resolution. While the computational and communication complexity of the backtracking based approaches is well understood, the tradeoffs in complexity involved in moving toward mediation based approaches are not. In this paper we comprehensively reexamine the space of mediation based approaches for DCSP and fill gaps in existing frameworks with new strategies. We present different mediation session selection rules, including a rule that favors smaller mediation sessions, and different mediation strategies, including a decentralized hybrid strategy based on ABT. We present empirical results on solvable 3-coloring and random binary DCSP problems, that accurately capture the computational and communication tradeoffs between ABT and various mediation based approaches. Our results confirm that under some circumstances the newly presented strategies dominate previously proposed techniques.

20 pages

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