We present an algorithm that quickly finds optimal plans for unforeseen agent preferences within graph-based planning domains where actions have deterministic outcomes and action ...
Despite the recent resurgence of interest in learning methods for planning, most such efforts are still focused exclusively on classical planning problems. In this work, we invest...
In the sequel we consider the job shop scheduling problem with uncertain durations represented as triangular fuzzy numbers. We propose a new neighbourhood structure for local sear...
Autonomous systems operating in real-world environments must plan, schedule, and execute missions while robustly adapting to uncertainty and disturbance. One way to mitigate the e...
This document formalizes and discusses the implementation of a new, more efficient probabilistic plan recognition algorithm called Yet Another Probabilistic Plan Recognizer, (Yapp...
Christopher W. Geib, John Maraist, Robert P. Goldm...
The causal graph is a directed graph that describes the variable dependencies present in a planning instance. A number of papers have studied the causal graph in both practical an...
In the last decades, there has been an increasing interest in the connection between planning and constraint programming. Several approaches were used, leading to different forms ...
Researchers have developed a huge number of algorithms to solve classical planning problems. We provide a way to use these algorithms, unmodified, to generate strong-cyclic soluti...
Ugur Kuter, Dana S. Nau, Elnatan Reisner, Robert P...
We consider the Resource-Constrained Project Scheduling Problem with minimal and maximal time lags under resource and duration uncertainties. To manage resource uncertainties, we ...