Automatically acquiring control-knowledge for planning, as it is the case for Machine Learning in general, strongly depends on the training examples. In the case of planning, examp...
We introduce the Scanalyzer planning domain, a domain for classical planning which models the problem of automatic greenhouse logistic management. At its mathematical core, the Sc...
Divide-and-Evolve (DaE) is an original “memeticization” of Evolutionary Computation and Artificial Intelligence Planning. However, like any Evolutionary Algorithm, DaE has se...
We present a novel approach to multiagent planning for self-interested agents. The main idea behind our approach is that multiagent planning systems should be built upon (single-a...
Roman van der Krogt, Nico Roos, Mathijs de Weerdt,...
We define the robustness of a sequential plan as the probability that it will execute successfully despite uncertainty in the execution environment. We consider a rich notion of u...