Examining Coordination Tradeoffs in Distributed Constraint Satisfaction Problems (DCSPs)

Abstract

Distributed Constraint Satisfaction Problems (DCSPs) provide a model to capture a broad range of cooperative multi-agent problem solving settings. Researchers have generally pro- posed two different sets of approaches for solving DCSPs, backtracking based approaches, such as Asynchronous Backtracking (ABT), and mediation based approaches, such as Asyn- chronous Partial Overlay (APO). These sets of approaches differ in the levels of coordination employed during conflict resolution. While the computational and communication complex- ity 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 com- prehensively reexamine the space of mediation based approaches for DCSP and fill gaps in existing frameworks with new strategies. We present different mediation session selec- tion rules, including a rule that favors smaller mediation sessions, and different mediation strategies, including a decentralized hybrid strategy based on ABT. We present empirical re- sults on solvable 3-coloring and random binary DCSP problems, that accurately capture the computational and communication tradeoffs between ABT and various mediation based ap- proaches. Our results confirm that under some circumstances the newly presented strategies dominate previously proposed techniques.