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Temporal Reasoning Based on SemiIntervals
, 1992
"... A generalization of Allen's intervalbased approach to temporal reasoning is presented. The notion of `conceptual neighborhood' of qualitative relations between events is central to the presented approach. Relations between semiintervals rather than intervals are used as the basic units of knowledg ..."
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Cited by 234 (14 self)
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A generalization of Allen's intervalbased approach to temporal reasoning is presented. The notion of `conceptual neighborhood' of qualitative relations between events is central to the presented approach. Relations between semiintervals rather than intervals are used as the basic units of knowledge. Semiintervals correspond to temporal beginnings or endings of events. We demonstrate the advantages of reasoning on the basis of semiintervals: 1) semiintervals are rather natural entities both from a cognitive and from a computational point of view; 2) coarse knowledge can be processed directly; computational effort is saved; 3) incomplete knowledge about events can be fully exploited; 4) incomplete inferences made on the basis of complete knowledge can be used directly for further inference steps; 5) there is no tradeoff in computational strength for the added flexibility and efficiency; 6) for a natural subset of Allen's algebra, global consistency can be guaranteed in polynomial time; 7) knowledge about relations between events can be represented much more compactly.
Supporting ValidTime Indeterminacy
 ACM Transactions on Database Systems
, 1998
"... In validtime indeterminacy it is known that an event stored in a database did in fact occur, but it is not known exactly when. In this paper we extend the SQL data model and query language to support validtime indeterminacy. We represent the occurrence time of an event with a set of possible insta ..."
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Cited by 86 (17 self)
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In validtime indeterminacy it is known that an event stored in a database did in fact occur, but it is not known exactly when. In this paper we extend the SQL data model and query language to support validtime indeterminacy. We represent the occurrence time of an event with a set of possible instants, delimiting when the event might have occurred, and a probability distribution over that set. We also describe query language constructs to retrieve information in the presence of indeterminacy. These constructs enable users to specify their credibility in the underlying data and their plausibility in the relationships among that data. A denotational semantics for SQL’s select statement with optional credibility and plausibility constructs is given. We show that this semantics is reliable, in that it never produces incorrect information, is maximal, in that if it were extended to be more informative, the results may not be reliable, and reduces to the previous semantics when there is no indeterminacy. Although the extended data model and query language provide needed modeling capabilities, these extensions appear initially to carry a significant execution cost. A contribution of this paper is to demonstrate that our approach is useful and practical. An efficient representation of validtime indeterminacy and efficient query processing algorithms are provided. The cost of
Possibilistic Constraint Satisfaction Problems or "How to handle soft constraints ?"
 In Proc. 8th Conf. of Uncertainty in AI
, 1992
"... Many AI synthesis problems such as planning or scheduling may be modelized as constraint satisfaction problems (CSP). A CSP is typically defined as the problem of finding any consistent labeling for a fixed set of variables satisfying all given constraints between these variables. However, for many ..."
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Cited by 84 (8 self)
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Many AI synthesis problems such as planning or scheduling may be modelized as constraint satisfaction problems (CSP). A CSP is typically defined as the problem of finding any consistent labeling for a fixed set of variables satisfying all given constraints between these variables. However, for many real tasks such as jobshop scheduling, timetable scheduling, design..., all these constraints have not the same significance and have not to be necessarily satisfied. A first distinction can be made between hard constraints, which every solution should satisfy and soft constraints, whose satisfaction has not to be certain. In this paper, we formalize the notion of possibilistic constraint satisfaction problems that allows the modeling of uncertainly satisfied constraints. We use a possibility distribution over labelings to represent respective possibilities of each labeling. Necessityvalued constraints allow a simple expression of the respective certainty degrees of each constraint. The main advantage of our approach is its integration in the CSP technical framework. Most classical techniques, such as Backtracking (BT), arcconsistency enforcing (AC) or Forward Checking have been extended to handle possibilistics CSP and are effectively implemented. The utility of our approach is demonstrated on a simple design problem.
Possibility theory in constraint satisfaction problems: Handling priority, preference and uncertainty
 Applied Intelligence
, 1996
"... In classical Constraint Satisfaction Problems (CSPs) knowledge is embedded in a set of hard constraints, each one restricting the possible values of a set of variables. However constraints in real world problems are seldom hard, and CSP's are often idealizations that do not account for the preferenc ..."
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Cited by 74 (13 self)
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In classical Constraint Satisfaction Problems (CSPs) knowledge is embedded in a set of hard constraints, each one restricting the possible values of a set of variables. However constraints in real world problems are seldom hard, and CSP's are often idealizations that do not account for the preference among feasible solutions. Moreover some constraints may have priority over others. Lastly, constraints may involve uncertain parameters. This paper advocates the use of fuzzy sets and possibility theory as a realistic approach for the representation of these three aspects. Fuzzy constraints encompass both preference relations among possible instanciations and priorities among constraints. In a Fuzzy Constraint Satisfaction Problem (FCSP), a constraint is satisfied to a degree (rather than satisfied or not satisfied) and the acceptability of a potential solution becomes a gradual notion. Even if the FCSP is partially inconsistent, best instanciations are provided owing to the relaxation of ...
Fuzzy Constraints in JobShop Scheduling
 Journal of Intelligent Manufacturing
, 1995
"... : This paper proposes an extension of the constraintbased approach to jobshop scheduling, that accounts for the flexibility of temporal constraints and the uncertainty of operation durations. The set of solutions to a problem is viewed as a fuzzy set whose membership function reflects preference. ..."
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Cited by 53 (9 self)
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: This paper proposes an extension of the constraintbased approach to jobshop scheduling, that accounts for the flexibility of temporal constraints and the uncertainty of operation durations. The set of solutions to a problem is viewed as a fuzzy set whose membership function reflects preference. This membership function is obtained by an egalitarist aggregation of local constraintsatisfaction levels. Uncertainty is qualitatively described is terms of possibility distributions. The paper formulates a simple mathematical model of jobshop scheduling under preference and uncertainty, relating it to the formal framework of constraintsatisfaction problems in Artificial Intelligence. A combinatorial search method that solves the problem is outlined, including fuzzy extensions of wellknown lookahead schemes. 1. Introduction There are traditionally three kinds of approaches to jobshop scheduling problems: priority rules, combinatorial optimization and constraint analysis. The first kind ...
A Survey on Temporal Reasoning in Artificial Intelligence
, 1994
"... The notion of time is ubiquitous in any activity that requires intelligence. In particular, several important notions like change, causality, action are described in terms of time. Therefore, the representation of time and reasoning about time is of crucial importance for many Artificial Intelligenc ..."
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Cited by 42 (4 self)
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The notion of time is ubiquitous in any activity that requires intelligence. In particular, several important notions like change, causality, action are described in terms of time. Therefore, the representation of time and reasoning about time is of crucial importance for many Artificial Intelligence systems. Specifically during the last 10 years, it has been attracting the attention of many AI researchers. In this survey, the results of this work are analysed. Firstly, Temporal Reasoning is defined. Then, the most important representational issues which determine a Temporal Reasoning approach are introduced: the logical form on which the approach is based, the ontology (the units taken as primitives, the temporal relations, the algorithms that have been developed,. . . ) and the concepts related with reasoning about action (the representation of change, causality, action,. . . ). For each issue the different choices in the literature are discussed. 1 Introduction The notion of time i...
Knowledgebased production management: Approaches, results and prospects
 Production Planning & Control
, 1992
"... ..."
Exploiting Temporal Uncertainty in Parallel and Distributed Simulations
 in Proceedings of the 13th Workshop on Parallel and Distributed Simulation
, 1999
"... Most work to date in parallel and distributed discrete event simulation is based on assigning precise time stamps to events, and time stamp order event processing. An alternative approach is examined where modelers use time intervals rather than precise time stamps to specify uncertainty as to wh ..."
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Cited by 29 (4 self)
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Most work to date in parallel and distributed discrete event simulation is based on assigning precise time stamps to events, and time stamp order event processing. An alternative approach is examined where modelers use time intervals rather than precise time stamps to specify uncertainty as to when events occur. Partial orderings called approximate time (AT) and approximate time causal (ATC) order are proposed and synchronization algorithms developed that exploit these specifications to yield more efficient execution on parallel and distributed computers. Performance measurements of the ATordering mechanism on a cluster of workstations demonstrate as much as twentyfold performance improvement compared to time stamp ordering with negligible impact on the results computed by the simulation. The context for much of this work is federated simulation systems that provided the initial motivation for this work. These results demonstrate that exploiting temporal uncertainty inhere...
Probabilistic Temporal Databases, I: Algebra
"... ... In this paper, we first introduce the syntax of TemporalProbabilistic (TP) relations and then show how they can be converted to an explicit, significantly more spaceconsuming form called Annotated Relations. We then present a Theoretical Annotated Temporal Algebra (TATA). Being explicit, TATA ..."
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Cited by 26 (6 self)
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... In this paper, we first introduce the syntax of TemporalProbabilistic (TP) relations and then show how they can be converted to an explicit, significantly more spaceconsuming form called Annotated Relations. We then present a Theoretical Annotated Temporal Algebra (TATA). Being explicit, TATA is convenient for specifying how the algebraic operations should behave, but is impractical to use because annotated relations are overwhelmingly large. Next, we
A fuzzy model for representing uncertain, subjective and vague temporal knowledge in ontologies
 In Proceedings of the International Conference on Ontologies, Databases and Applications of Semantics, (ODBASE), volume 2888 of LNCS
, 2003
"... Abstract. Time modeling is a crucial feature in many application domains. However, temporal information often is not crisp, but is uncertain, subjective and vague. This is particularly true when representing historical information, as historical accounts are inherently imprecise. Similarly, we conje ..."
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Cited by 26 (3 self)
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Abstract. Time modeling is a crucial feature in many application domains. However, temporal information often is not crisp, but is uncertain, subjective and vague. This is particularly true when representing historical information, as historical accounts are inherently imprecise. Similarly, we conjecture that in the Semantic Web representing uncertain temporal information will be a common requirement. Hence, existing approaches for temporal modeling based on crisp representation of time cannot be applied to these advanced modeling tasks. To overcome these difficulties, in this paper we present fuzzy intervalbased temporal model capable of representing imprecise temporal knowledge. Our approach naturally subsumes existing crisp temporal models, i.e. crisp temporal relationships are intuitively represented in our system. Apart from presenting the fuzzy temporal model, we discuss how this model is integrated with the ontology model to allow annotating ontology definitions with time specifications. 1