Meta-level architectures for dynamic control of reasoning processes are quite powerful. In the literature many applications in reasoning systems modelling complex tasks are described, usually in a procedural manner. In this paper we present a semantic framework based on temporal partial logic to describe the dynamics of reasoning behaviour. Using these models the semantics of the behaviour of t...

The temporal boundaries of many real–world events are inherently vague. In this paper, we discuss the problem of qualitative temporal reasoning about such vague events. We show that several interesting reasoning tasks, such as checking satisfiability, checking entailment, and calculating the best truth value bound, can be reduced to reasoning tasks in a well–known point algebra with disjunction...

The research is based on the designing of Clinical Temporal Mediator for medical domain. The Clinical Temporal Mediator incorporates the concept of artificial intelligence for performing temporal reasoning tasks. The designing of reasoning system involves the implementation of various mathematical models of insulin-glucose metabolism. The reasoning system consists of three subsystems: Nuti-Diet...

Despite the ubiquity of time and temporal references in legal texts, their formal-ization has often been either disregarded or addressed in an ad hoc manner. In this paper we address this issue from the standpoint of the research done on temporal representation and reasoning in AI. We identify the temporal requirements of legal domains and propose a temporal representation framework for legal r...

Symbolic cognitive architectures typically have an implicit representation of time. Actions taken occur in a sequential order, but reasoning about specific temporal relationships among objects and events is typically beyond the architecture’s capabilities. In this paper, we describe an extension of the Icarus architecture to include an episodic belief memory and an explicit representation of te...

Many artificial intelligence tasks (e.g., planning, situation assessment, scheduling) require reasoning about events in time. Temporal constraint networks offer an elegant and often computationally efficient framework for formulation and solution of such temporal reasoning tasks. Temporal data and knowledge available in some domains is necessarily imprecise e.g., as a result of measurement erro...

Temporal knowledge representation and reasoning is a major research field in Artificial Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to model and process time and calendar data is essential for many applications like appointment scheduling, planning, Web services, temporal and active database systems, adaptive Web applications, and mobile computing applic...

Temporal Action Logic is a well established logical formalism for reasoning about action and change using an explicit time representation that makes it suitable for applications that involve complex temporal reasoning. We take advantage of constraint satisfaction technology to facilitate such reasoning through temporal constraint networks. Extensions are introduced that make generation of actio...

Temporal knowledge representation and reasoning is a major research field in Artificial Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to model and process time and calendar data is essential for many applications like appointment scheduling, planning, Web services, temporal and active database systems, adaptive Web applications, and mobile computing applic...

Reason maintenance systems and tem poral reasoning systems are among the most prominent application independent support systems used for complex AI ap plications and there are many applications that need both support for logical and temporal reasoning Apparently it is not enough to just provide two isolated sup port modules The logical and temporal subsystems have to be coupled in the right way...