We combine quantified differential dynamic logic (QdL) for reasoning about the possible behavior of distributed hybrid systems with temporal logic for reasoning about the temporal behavior during their operation. Our logic supports verification of temporal and non-temporal properties of distributed hybrid systems and provides a uniform treatment of discrete transitions, continuous evolution, an...

It has recently been shown that syllogistic reasoning engages two dissociable neural systems. Reasoning about familiar situations engages a frontal-temporal lobe system, whereas formally identical reasoning tasks involving unfamiliar situations recruit a frontal-parietal visuospatial network. These two systems may correspond to the "heuristic" and "formal" methods, respectively, postulated by c...

Temporal reasoning is an important task in many areas of computer science including planning, scheduling, temporal databases and instruction optimisation for compilers. Given a knowledge-base consisting of temporal relations, the main reasoning problem is to determine whether the knowledge-base is satisfiable, i.e., is there a scenario which is consistent with the information provided. However,...

We discuss recent research involving the temporal reasoning system Tachyon, which we axe developing at GE, and its application to mixed-initiative planning in the ARPA/Rome Laboratory Planning Initiative (ARPI). Tachyon is an implementation of constraint-based model for representing and reasoning aboub qualitative and quantitative aspects of time. It’s data model provides substantial expressive...

The Disjunctive Fuzzy Temporal Constraint Network (DFTCN) model is a framework that allows reasoning with fuzzy qualitative and quantitative complex temporal constraints. However, its general complexity is exponential. In this work, we review methods that can reduce this complexity, based on graph topology and preprocessing. The final goal is to integrate all these methods into a general tool f...

In this paper we propose the combination of modularity and temporal reasoning using logic programming as common ground. Moreover, we consider that the usage of a given module is influenced by temporal constraints, i.e. modularity and temporal reasoning are strongly connected. Besides illustrative examples, we also present the operational semantics and corresponding compiler for this language.

Using Semantic-Web specifications to represent temporal information in clinical narratives is an important step for temporal reasoning and answering time-oriented queries. Existing temporal models are either not compatible with the powerful reasoning tools developed for the Semantic Web, or designed only for structured clinical data and therefore are not ready to be applied on natural-language-...

Qualitative spatio-temporal reasoning is an active research area in Artificial Intelligence. In many situations there is a need to reason about intertemporal qualitative spatial relations, i.e. qualitative relations between spatial regions at different time-points. However, these relations can never be explicitly observed since they are between regions at different time-points. In applications ...

In this paper we develop a new modal logic for spatial reasoning called Temporalized Propositional Neighborhood Logic, which is the result of the application of a known technique called temporalization to a known temporal logic for spatial reasoning (PNL). We will show that our logic is expressive enough to formalize interesting spatial statements and that it is decidable in NEXPTIME.

Artificial agents participating in public traffic must respect rules that regulate traffic. Rule sets are commonly formulated in natural language using purely qualitative terms. We present a case study on how to realize rule compliant agent control in the domain of sea navigation by using qualitative spatial reasoning techniques.