We present an AI called Visuo that guesses quantitative visuospatial magnitudes (e.g., heights, lengths) given adjective-noun pairs as input (e.g., “big hat”). It uses a database of tagged images as memory and infers unexperienced magnitudes by analogy with semanticallyrelated concepts in memory. We show that transferring width-height ratios from a semantically-related concept yields significan...

The study of fuzzy intervals is of particular interest in temporal database research. In order to optimize the storage of fuzzy temporal intervals, some transformations have been proposed. In this paper we analyze the possibilistic evaluation of the ill-known temporal intervals. We propose a framework to deal with the evaluation of ill-known temporal intervals. It is shown how the reasoning beh...

We examined the use of hand gestures while people solved spatial reasoning problem in which they had to infer motion from static diagrams (mental animation problems). In Experiment 1, participants were asked to think aloud while solving mental animation problems. They gestured on more than 90% of problems, and most gestures expressed information about the component motions that was not stated i...

Temporal indeterminacy, the lack of specific knowledge about the timing of events, occurs often in temporal reasoning in practical applications and is connected to the concept of time granularity. Although logical properties of granularities have been described by several researchers in the literature, the implications of temporal indeterminacy and granularities for probabilistic representation...

We describe a prototype toolkit for reasoning about Graphical Interval Logic (GIL) speciications of concurrent systems. GIL is a visual temporal logic that is intended to be more intuitive and easier to use than standard textual temporal logics. The GIL toolkit helps system designers to create graphical speciications of concurrent systems, to verify properties of those systems from their specii...

Texts in natural language contain a lot of temporal information, both explicit and implicit. Verbs and temporal adjuncts carry most of the explicit information, but for a full understanding general world knowledge and default assumptions have to be taken into account. We will present a theory for describing the relation between, on the one hand, verbs, their tenses and adjuncts and, on the othe...

Temporal relational reasoning, the ability to link meaningful transformations of objects or entities over time, is a fundamental property of intelligent species. In this paper, we introduce an effective and interpretable network module, the Temporal Relation Network (TRN), designed to learn and reason about temporal dependencies between video frames at multiple time scales. We evaluate TRNequip...

The representation of temporal information has been in the center of intensive research activities over the years in the areas of knowledge representation, databases and more recently, the Semantic Web. The proposed approach extends the existing framework of representing temporal information in ontologies by allowing for representation of concepts evolving in time (referred to as “dynamic” info...

A temporal reasoning problem can often be naturally characterized as a collection of constraints with associated local preferences for times that make up the admissible values for those constraints. Globally preferred solutions to such problems emerge as a result of well-defined operations that compose and order temporal assignments. The overall objective of this work is a characterization of d...