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Planning in domains with temporal and numerical properties is an important research problem. One application of this is the resource production problem in real-time strategy (RTS)...
Hei Chan, Alan Fern, Soumya Ray, Nick Wilson, Chri...
Many of the benchmark domains in AI planning are tractable on an individual basis. In this paper, we seek a theoretical, domain-independent explanation for their tractability. We ...
We introduce the Linear Resource Temporal Network (LRTN), which consists of activities that consume or produce a resource, subject to absolute and relative metric temporal constra...
In this paper, we propose an extended local search framework to solve combinatorial optimization problems with data uncertainty. Our approach represents a major departure from sce...
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...
Several researchers have shown that the efficiency of value iteration, a dynamic programming algorithm for Markov decision processes, can be improved by prioritizing the order of...
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 ...
Decomposition has proved an effective strategy in planning, with one decomposition-based planner, SGPLAN, exhibiting strong performance in the last two IPCs. By decomposing planni...