Summary: 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.