SymDPOP: Adapting DPOP to exploit partial symmetries

This work proposes a new approach to dealing with symmetries in Distributed Constraint Optimisation Problems by adapting the DPOP algorithm [1]. In contrast to an already proposed distributed preprocessing method leading to a problem redefinition [2], we present here a method that exploits the structure of DFS trees, with no explicit redefinition of the problem. We exhibit the flexibility in the symmetry detection that this algorithm offers, then compare its performance with DPOP and the aforementioned preprocessing method. We demonstrate that SymDPOP significantly cuts down the total volume of communication spent on symmetric and partially symmetric problems, the latter being problems containing symmetric subproblems. We also stress the fact that SymDPOP minimises the overhead of symmetry detection by keeping the total volume of communication below that of DPOP.