The distributed constraint satisfaction problem (DisCSP) can be viewed as a 4-tuple (X, D, C, A), where X is a set of n variables, D is a set of n domains (one domain for each of the n variables), C is a set of constraints that constrain the values that can be assigned to the n variables, and A is a set of agents for which the variables and constraints are distributed. The objective in solving a DisCSP is to allow the agents in A to develop a consistent distributed solution by means of message passing. In this paper, we present an evolutionary society of hill-climbers (ESoHC) that outperforms a previously developed algorithm for solving randomly generated DisCSPs that are composed of asymmetric constraints on a test suite of 2,800 distributed asymmetric constraint satisfaction problems.
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