IndiGolog: Execution of guarded action theories
Sebastian Sardiña · TSpace (University of Toronto) · 2000
In AI, the problem of selecting (high-level) actions in dynamic and not completely pre-dictable environments translates into the problem of designing controllers that can map sequence of observations into actions so that certain goals are achieved. One approach to high-level controllers is high-level programming. Basically, we imag-ine a system executing a high-level program with respect to a background theory of action. Whereas the background theory describes the characteristics of the domain (ac-tion preconditions, action effects and non-effects, etc.), the high-level program provides strong, but usually incomplete, clues about what the desired sequence of actions should be like. The work presented here combines two recent, but unexplored ideas: Guarded Action Theories and Incremental Program Execution. The result is a new high-level program-ming language, which we call IndiGolog, whose programs, compared with previous lan-guages, are executed in a more practical way with respect to more open-world theories. We provide a theoretical exploration of both guarded theories and program execution, and develop a Prolog implementation for IndiGolog.