The project is developing a framework for efficient reasoning about effects of actions in temporal action theories (TAT) with incomplete information and state constraints in the form of static causal laws. To cope with the high complexity of temporal reasoning and planning problems, the project develops and exploits an approximation theory for query answering and planning in TAT. This theory is being used as the basis for sound and efficient algorithms for hypothetical reasoning and planning.
This framework guides the development of state-of-the-art temporal conformant planners, robust in the face of a variety of contingencies, which can deal with various classes of preferences. Techniques developed will application, for example, in the composition of web services for comparative data analysis in evolutionary biology.
