Automatic Vehicle Checking Agent (VCA)

TL;DR

This paper proposes a conceptual model for an intelligent vehicle checking system using various agent types, with metrics and calibration methods to evaluate and develop such systems.

Contribution

It introduces a novel multi-agent framework for automatic vehicle checking and suggests performance metrics and calibration methods.

Findings

Defined a multi-agent system architecture for VCA

Proposed metrics for evaluating VCA performance

Suggested calibration data and testing facilities

Abstract

A definition of intelligence is given in terms of performance that can be quantitatively measured. In this study, we have presented a conceptual model of Intelligent Agent System for Automatic Vehicle Checking Agent (VCA). To achieve this goal, we have introduced several kinds of agents that exhibit intelligent features. These are the Management agent, internal agent, External Agent, Watcher agent and Report agent. Metrics and measurements are suggested for evaluating the performance of Automatic Vehicle Checking Agent (VCA). Calibrate data and test facilities are suggested to facilitate the development of intelligent systems.