Authors:
Amel Ben Othmane
;
Andrea Tettamanzi
;
Serena Villata
and
Nhan Le Thanh
Affiliation:
Université Côte d'Azur, France
Keyword(s):
Region Connection Calculus, Allen’s Intervals, Fuzzy Sets.
Related
Ontology
Subjects/Areas/Topics:
Agent Models and Architectures
;
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
Agent-based recommender systems have been exploited in the last years to provide informative suggestions
to users, showing the advantage of exploiting components like beliefs, goals and trust in the recommendations’
computation. However, many real-world scenarios, like the traffic one, require the additional feature of
representing and reasoning about spatial and temporal knowledge, considering also their vague connotation.
This paper tackles this challenge and introduces CARS, a spatio-temporal agent-based recommender system
based on the Belief-Desire-Intention (BDI) architecture. Our approach extends the BDI model with spatial
and temporal information to represent and reason about fuzzy beliefs and desires dynamics. An experimental
evaluation about spatio-temporal reasoning in the traffic domain is carried out using the NetLogo platform,
showing the improvements our recommender system introduces to support agents in achieving their goals.