Using Object Influence Areas to Quantitatively Deal with Neighborhood and Perception in Route Descriptions

Authors:
Bernard Moulin;Driss Kettani;Benjamin Gauthier;Walid Chaker
Affiliations:
-;-;-;-
Venue:
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Year:
2000

Citing 8
Cited 0

Commonsense reasoning about causality: deriving behavior from structure

Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Temporal reasoning based on semi-intervals

Artificial Intelligence
Maintaining knowledge about temporal intervals

Communications of the ACM
Qualitative Representation of Spatial Knowledge

Qualitative Representation of Spatial Knowledge
From Knowledge to Words to Wayfinding: Issues in the Production and Comprehension of Route Directions

COSIT '97 Proceedings of the International Conference on Spatial Information Theory: A Theoretical Basis for GIS
Structuring Space with Image Schemata: Wayfinding in Airports as a Case Study

COSIT '97 Proceedings of the International Conference on Spatial Information Theory: A Theoretical Basis for GIS
A Spatial Model Based on the Notions of Spatial Conceptual Map and of Object's Influence Areas

COSIT '99 Proceedings of the International Conference on Spatial Information Theory: Cognitive and Computational Foundations of Geographic Information Science
A Wayfinding Application Based on the Influence Area Spatial Model

Proceedings of the Twelfth International Florida Artificial Intelligence Research Society Conference

Quantified Score

Hi-index	0.00

Visualization

Abstract

In the GRAAD project we are developing a knowledge-based system able of determine routes in a simulated urban environment and to generate natural language descriptions which are not distinguishable from those produced by human beings in similar conditions. In this paper, we present a new spatial model whose topology is based on the notion of object's influence areas. An influence area is a portion of space that people mentally build around spatial objects to take into account neighborhood. We use this notion to formally define the properties of neighborhood, orientation and distance in a qualitative way. We also introduce the notion of an object's perception area, an area gathering all the locations from which an object can be perceived. Based on these notions, we describe two modules of the GRAAD System that are able to find routes in a simulated urban environment and to generate route descriptions in natural language which are analog to those created by people.