Affiliations: [a] School of Computer Science, University of Waterloo, Waterloo, ON, Canada | [b] School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada | [c] School of Computer Science and Engineering, Nanyang Technological University, Singapore
Correspondence:
[*]
Corresponding author: Robin Cohen, School of Computer Science, University of Waterloo, Waterloo, ON, Canada. E-mail:[email protected]
Abstract: In this paper, we describe a framework used for decision support
by intelligent agents in transportation environments: assisting
drivers in making effective travel decisions based on traffic
reports provided by peers. Operating with a proposed multi-faceted
trust model for judging the trustworthiness of the peers and their
reports, we introduce an ontological representation that makes
possible the kind of detailed trust modeling essential for the
decision making. In so doing, we are offering a framework that
clarifies the representation and the messaging required to enable
the trust-based decision making to be run. We demonstrate how this
representation assists in the clarification of knowledge
provenance and how it can be employed in real-time. We outline the
effectiveness of the framework through an extensive simulation of
travel time by vehicles controlled with our specific trust
modeling. As such, we are able to demonstrate the importance of
our ontological representation in enabling multi-faceted trust
modeling, leading to important advice for the field of multiagent
trust for decision support.
