While much work on learning in planning focused on learning domain physics (i.e., action models), and search control knowledge, little attention has been paid towards learning use...
Nan Li, William Cushing, Subbarao Kambhampati, Sun...
Relaxations based on (either complete or partial) ignoring delete effects of the actions provide the basis for some seminal classical planning heuristics. However, the palette of ...
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-calle...
High-level controllers that operate robots in dynamic, uncertain domains are concerned with at least two reasoning tasks dealing with the effects of noisy sensors and effectors: T...
A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...