(No)good Recording and ROBDDs for Solving Structured (V)CSPs

It was shown that constraint satisfaction problems (CSPs) with a low width can be solved efficiently by structural methods. However, these methods often present an important drawback: they generally require a large amount of memory space, what makes their use difficult or impossible. For instance, the BTD method solves efficiently difficult instances thanks to the recording of goods and nogoods. As this recording may require an exponential memory size, the exploitation of a compact data structure is crucial. In this paper, we propose to store (no)goods in binary decision diagrams (BDD). BDDs are data structures which efficiently represent informations in a compact and canonical form. Finally, we assess the practical interest of this tradeoff which allows to save space memory and consequently to solve problems that cannot be solved without BDDs