Uncertainty is commonly encountered in temporal scheduling and planning problems, and
can often lead to over-constrained situations. Previous relaxation algorithms for over …

Over-constrained temporal problems are commonly encountered while operating
autonomous and decision support systems. An intelligent system must learn a human's …

When scheduling tasks for field-deployable systems, our solutions must be robust to the
uncertainty inherent in the real world. Although human intuition is trusted to balance reward …

Over-subscription, that is, being assigned too many things to do, is commonly encountered
in temporal scheduling problems. As human beings, we often want to do more than we can …

We describe a strong connection between maximally satisfiable and minimally unsatisfiable
subsets of constraint systems. Using this relationship, we develop a two-phase algorithm …

The satellite-scheduling problem represents an interesting field to test non-conventional
temporal solvers because scheduling-problems are inherently over-constrained and …

We present an algorithm and pruning techniques for efficiently finding optimal solutions to
over-constrained instances of the Disjunctive Temporal Problem with Preferences (DTPP) …

In this paper, we consider both the modelling and optimization of preferences in problems of
constraint-based temporal reasoning. The Disjunctive Temporal Problems with Preferences …

We present a method for applying local search to overconstrained instances of the
Disjunctive Temporal Problem (DTP). Our objective is to generate high quality solutions (ie …

We present a new efficient algorithm for obtaining utilitarian optimal solutions to Disjunctive
Temporal Problems with Preferences (DTPPs). The previous state-of-the-art system …