Planning With Transaction Logic

Automated planning has been the subject of intensive research and is at the core of several areas of AI, including intelligent agents and robotics. In this paper, we argue that Transaction Logic is a natural specification language for planning algorithms, which enables one to see further afield and thus discover better and more general solutions than using one-of-a-kind formalisms. Specifically, we take the well-known STRIPS planning strategy and show that Transaction Logic lets one specify the STRIPS planning algorithm easily and concisely, and to prove its completeness. Moreover, extensions to allow indirect effects and to support action ramifications come almost for free. Finally, the compact and clear logical formulation of the algorithm made possible by this logic is conducive to fruitful experimentation. To illustrate this, we show that a rather simple modification of the STRIPS planning strategy is also complete and yields speedups of orders of magnitude.