Author name cluster
Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.
TIME Conference 2009 Conference Paper
Interval algebra networks are traditionally defined over finite intervals. In this paper, we relax this restriction by allowing one or more of the intervals involved to be infinite. We then show how algorithms developed for solving interval algebra networks with finite intervals can be used, with minor modifications, in the infinite case.
TIME Conference 2006 Conference Paper
A probabilistic interval algebra (PIA) network is an interval algebra network with probabilities associated with the labels on an edge. The probabilities on each edge sum to 1. A solution is a consistent scenario where the product of the probabilities associated with each unique edge label is maximized. In this paper we investigate previous PIA network solution algorithms, and propose new ones. Our first algorithm is based on best first search and guarantees to output the optimal solution. However, this algorithm is only feasible for toy problems. We augment the algorithm with three heuristics. Although our proposed algorithm does not guarantee an optimal solution, it is very useful in practice. Good solutions can be generated quickly
TIME Conference 2005 Conference Paper
We exploit the fact that qualitative interval algebra (IA) network problems are finite domain CSPs. We show how to convert a qualitative IA network into an equivalent binary CSP problem with finite integer domains. The main benefit is that standard binary CSP solution techniques can be used. Once a solution is found, the transformations can be applied in reverse to generate a solution to the original IA network. We also prove that it is not the case that all finite domain binary CSP problems have an equivalent qualitative IA network counterpart.
TIME Conference 2004 Conference Paper
A probabilistic temporal interval network is a constraint satisfaction problem where the nodes are temporal intervals and the edges are uncertain interval relations. We attach a probability to each of Allen's basic interval relations. An uncertain relation between two temporal intervals is represented as a disjunction of Allen's probabilistic basic relations. Using the operations of inversion, composition, and addition, defined for this probabilistic representation, we present a path consistency algorithm.
TIME Conference 2001 Conference Paper
We present a simple classification of temporal information based on truth value at the point level. Axioms are then derived for capturing temporal relationships and, strong and weak negation. The main advantage of our logic independent approach is that it becomes simpler for a user to define a first order temporal logic.
TIME Conference 1996 Conference Paper
The authors present a spatio-temporal ontology suitable for representing and reasoning about the qualitative motion of rigid bodies. This simple ontology provides a uniform treatment of motion in one, two, and three dimensional space. A succinct axiomatization is provided capturing the ontology. This first order logic is based on the transition of topological relations between objects.
TIME Conference 1994 Conference Paper
TIME Conference 1994 Conference Paper
TIME Conference 1994 Conference Paper
TIME Conference 1994 Conference Paper
We formally define a first order logic that is suitable for representing and reasoning about uncertain temporal domains. The logic can represent both interval and point based qualitative and quantitative information. We provide a syntax, semantics, and axiomatization for the logic. We then describe the constraint logic programming implementation of the logic. The implementation, along with its formal specification, is suitable for tackling real world temporal problems.