L. Vila’s research while affiliated with Artificial Intelligence Research Institute and other places

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Publications (6)


Temporal Constraints: A Survey
  • Article

June 1998

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22 Reads

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128 Citations

Constraints

Eddie Schwalb

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Lluís Vila

Temporal Constraint Satisfaction is an information technology useful for representing and answering queries about temporal occurrences and temporal relations between them. Information is represented as a Constraint Satisfaction Problem (CSP) where variables denote event times and constraints represent the possible temporal relations between them. The main tasks are two: (i) deciding consistency, and (ii) answering queries about scenarios that satisfy all constraints. This paper overviews results on several classes of Temporal CSPs: qualitative interval, qualitative point, metric point, and some of their combinations. Research has progressed along three lines: (i) identifying tractable subclasses, (ii) developing exact search algorithms, and (iii) developing polynomial-time approximation algorithms. Most available techniques are based on two principles: (i) enforcing local consistency (e.g. path-consistency) and (ii) enhancing naive backtracking search.


Summarizing CSP Hardness with Continuous Probability Distributions.
  • Conference Paper
  • Full-text available

January 1997

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281 Reads

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64 Citations

We present empirical evidence that the distribution ofeffort required to solve CSPs randomly generated atthe 50% satisfiable point, when using a backtrackingalgorithm, can be approximated by two standard familiesof continuous probability distribution functions.Solvable problems can be modelled by the Weibull distribution,and unsolvable problems by the lognormaldistribution. These distributions fit equally well overa variety of backtracking based algorithms.1. IntroductionSeveral key...

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Summarizing CSP hardness with continuous pro distributions

January 1997

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24 Reads

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5 Citations

We present empirical evidence that the distribution of effort required to solve CSPs randomly generated at the 50% satisfiable point, when using a backtracking algorithm, can be approximated by two standard fam-ilies of continuous probability distribution functions. Solvable problems can be modelled by the Weibull dis-tribution, and unsolvable problems by the lognormal distribution. These distributions fit equally well over a variety of backtracking based algorithms.


Logic programming with temporal constraints

June 1996

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7 Reads

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8 Citations

Combines logic programming and temporal constraint processing techniques in a language called TCLP (Temporal Constraint Logic Programming), which augments logic programs with temporal constraints. Known algorithms for processing disjunctions in temporal constraint networks are applied. We identify a decidable fragment called Simple TCLP, which can be viewed as extending Datalog with limited functions to accommodate intervals of occurrence and temporal constraints between them. Some of the restrictions introduced by Simple TCLP are overcome by a syntactic structure which provides it with the benefits of reification. The latter allows quantification on temporal occurrences and relation symbols


A theory of time and temporal incidence based on instants andperiods

June 1996

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29 Reads

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3 Citations

Time is fundamental in representing and reasoning about changing domains. A proper temporal representation requires characterizing two notions: (1) time itself, and (2) temporal incidence, i.e. the domain-independent properties for the truth-value of fluents and events throughout time. There are some problematic issues, such as the expression of instantaneous events and instantaneous holding of fluents, the specification of the properties for the temporal holding of fluents, and the “dividing instant problem”. This paper presents a theory of time and temporal incidence which is more natural than its predecessors and satisfactorily addresses the issues above. Our theory of time, called ℐ𝒫 (Instants and Periods), is based on having instants and periods at equal levels. We define a theory of temporal incidence upon it, whose main original feature is the distinction between continuous and discrete fluents


A theory of time and temporal incidence based on instants and periods

May 1996

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9 Reads

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21 Citations

Time is fundamental in representing and reasoning about changing domains. A proper temporal representation requires characterizing two notions: (1) time itself, and (2) temporal incidence, i.e. the domain-independent properties for the truth-value of fluents and events throughout time. There are some problematic issues, such as the expression of instantaneous events and instantaneous holding of fluents, the specification of the properties for the temporal holding of fluents, and the "dividing instant problem". This paper presents a theory of time and temporal incidence which is more natural than its predecessors and satisfactorily addresses the issues above. Our theory of time, called /spl Iscr//spl Pscr/ (Instants and Periods), is based on having instants and periods at equal levels. We define a theory of temporal incidence upon it, whose main original feature is the distinction between continuous and discrete fluents.

Citations (6)


... Yet there is an uncommon but powerful feature of time boundaries, expounded in section 4.1, that is their ability to coincide. The "existential priority" of chronoids over time boundaries and the notion of coincidence constitute major differences to usual dual time theories of points and intervals, such as IP (Vila, 1994(Vila, , 2005. 3 The second theory developed, BT R , addresses chronoids, time boundaries, and in addition mereological sums of the entities of each kind, called time regions and time boundary regions, respectively. Due to technical reasons, BT C is not literally a subtheory of BT R , but there is a natural interpretation into BT R . ...

Reference:

Axiomatic theories of the ontology of time in GFO
A theory of time and temporal incidence based on instants and periods
  • Citing Conference Paper
  • May 1996

... The study of the runtime distributions instead of just medians and means often provides a better characterization of search methods and much useful information in the design of algorithms. For instance, complete backtrack search methods exhibit fat and heavy-tailed behavior [47,41,23]. Fat-tailedness is based on the kurtosis of a distribution. ...

Summarizing CSP hardness with continuous pro distributions

... However, measures like the mean or the variance cannot capture the long-tailed behavior of difficult instances. Some authors (e. g., [FRV97,GS97,RF97]) thus shifted their focus to studying the runtime distributions of search algorithms, which helps to understand these methods better and draw meaningful conclusions for the design of new algorithms. ...

Summarizing CSP Hardness with Continuous Probability Distributions.