We study the complexity of sequentially-optimal classical planning, and discover new problem classes for whose such optimization is tractable. The results are based on exploiting ...
Due to its important practical applications, temporal planning is of great research interest in artificial intelligence. Yet most of the work in this area so far is limited in at...
We present three new complexity results for classes of planning problems with simple causal graphs. First, we describe a polynomial time algorithm that uses macros to generate pla...
This paper treats the problem of managing personal tasks, through an adaptation of the Squeaky Wheel Optimization (SWO) framework, enhanced with powerful heuristics and full const...
We present an any-time concurrent probabilistic temporal planner that includes continuous and discrete uncertainties and metric functions. Our approach is a direct policy search t...