The aim of this paper is to present a framework for developing intelligent agents that act in dynamic and unpredictable environments in a robust and efficient way. To achieve this ...
In this paper, a novel artificial potential function is proposed for planning the path of a robotic sensor in a partially observed environment containing multiple obstacles and mul...
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 ...
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
We present a case study in confronting the GPT generalpurpose planner with the challenging power supply restoration (PSR) benchmark for contingent planning. PSR is derived from a ...