Verification of multiple agent knowledge-based systems

The purpose of the paper is to extend verification tests to systems with multiple autonomous agent knowledge bases. In particular, the paper focuses on those unique inter-agent anomalies that are generated as we go from single agent systems to multiple agent systems. For example, consider one agent with the rule “if A then B” and a rule in another agent “if A then C”. In such a setting, the agents would be constantly at odds. Alternatively we might find the following rules in one agent (“if A then B” and “if C then A”), while another agent that interacts with that agent might have the rule (“if B then C”). With those two interacting rule bases a dialogue starting with “A” could cycle indefinitely. One potential approach to multiple agent systems is to compare the knowledge base of each subset of agents to determine the existence verification issues. Where the number of agents is small, this approach is feasible. However, for even medium size systems this approach explodes computationally. As a result, there is a need for alternative approaches. The paper finds that many of the multiple agent verification tests can be conducted on a meta rule set generated from all the rules contained in each of the agents´ knowledge bases thus minimizing computational effort. In addition, the paper finds that the property of agent “isolation” is an important verification criteria in multiple agent systems