Recently model checking representation and search techniques were shown to be efciently applicable to planning, in particular to non-deterministic planning. Such planning approaches use Ordered Binary Decision Diagrams (obdds) to encode a planning domainas a non-deterministic nite automatonand then apply fast algorithms frommodel checking to search for a solution. obdds can e ectively scale and can provide universal plans for complex planning domains. We are particularly interested in addressing the complexities arising in non-deterministic, multi-agent domains. In this article, we present umop, a new universal obdd-based planning framework for non-deterministic, multi-agent domains. We introduce a new planning domain description language, NADL, to specify non-deterministic, multi-agent domains. The language contributes the explicit de nition of controllable agents and uncontrollable environment agents. We describe the syntax and semantics of NADL and show how to build an e cient obdd...
Rune M. Jensen, Manuela M. Veloso