Cooperative Monitoring to Diagnose Multiagent Plans

Diagnosing the execution of a Multiagent Plan (MAP) means identifying and explaining action failures (i.e., actions that did not reach their expected effects). Current approaches to MAP diagnosis are substantially centralized, and assume that action failures are inde-pendent of each other. In this paper, the diagnosis of MAPs, executed in a dynamic and partially observable environment, is addressed in a fully distributed and asynchronous way; in addition, action failures are no longer assumed as independent of each other. The paper presents a novel methodology, named Cooperative Weak-Committed Moni-toring (CWCM), enabling agents to cooperate while monitoring their own actions. Coop-eration helps the agents to cope with very scarcely observable environments: what an agent cannot observe directly can be acquired from other agents. CWCM exploits nondetermin-istic action models to carry out two main tasks: detecting action failures and building trajectory-sets (i.e., structures representing the knowledge an agent has about the environ-ment in the recent past). Relying on trajectory-sets, each agent is able to explain its own action failures in terms of exogenous events that have occurred during the execution of the actions themselves. To cope with dependent failures, CWCM is coupled with a diagnostic engine that distinguishes between primary and secondary action failures. An experimental analysis demonstrates that the CWCM methodology, together with the proposed diagnostic inferences, are effective in identifying and explaining action failures even in scenarios where the system observability is significantly reduced. 1

Revising Description Logic Terminologies to Handle Exceptions: a First Step

Abstract. We propose a methodology to revise a Description Logic knowledge base when detecting exceptions. Our approach relies on the methodology for debugging a Description Logic terminology, addressing the problem of diagnosing incoherent ontologies by identifying a mini-mal subset of axioms responsible for an inconsistency. In the approach we propose, once the source of the inconsistency has been localized, the identified axioms are revised in order to obtain a consistent knowledge base including the detected exception. To this aim, we make use of a non-monotonic extension of the Description Logic ALC based on the com-bination of a typicality operator and the well established nonmonotonic mechanism of rational closure, which allows to deal with prototypical properties and defeasible inheritance.