Abstract
SummaryWe present a framework for the modelling, specification, and verification of ontology‐driven multi‐agent rule‐based systems (MASs). We assume that each agent executes in a separate process and that they communicate via message passing. The proposed approach makes use of abstract specifications to model the behaviour of some of the agents in the system and exploits information about the reasoning strategy adopted by the agents. Abstract specifications are given as Linear Temporal Logic (LTL) formulas which describe the external behaviour of the agents, allowing their temporal behaviour to be compactly modelled. Both abstraction and strategy have been combined in an automated model checking encoding tool Tovrba for rule‐based multi‐agent systems which allows the system designer to specify information about agents' interaction, behaviour, and execution strategy at different levels of abstraction. The Tovrba tool generates an encoding of the system for the Maude LTL model checker, allowing properties of the system to be verified.
Highlights
Rule-based systems have been studied for decades and traditionally rules have been used in theoretical computer science, databases, logic programming, and in particular, in artificial intelligence (AI), to describe expert systems, robot behavior, and behaviour of business
We use standard model checking techniques to verify interesting properties of such systems, and show how the Maude Linear Temporal Logic (LTL) model checker [15] can be used to verify properties including response-time guarantees of the form: if the system receives a query, a response will be produced within n time steps
The two main components of rule-based agents are the knowledge base (KB) which contains a set of first-order Horn-clause rules and the working memory (WM) which contains a set of facts that constitute the current state of the system
Summary
Rule-based systems have been studied for decades and traditionally rules have been used in theoretical computer science, databases, logic programming, and in particular, in artificial intelligence (AI), to describe expert systems, robot behavior, and behaviour of business. While rule-based systems are rapidly becoming an important component of Semantic Web application, the resulting system behaviour and the resources required to realize them, namely, how to ensure the correctness of rule-based designs (will a rule-based system produce the correct output for all legal inputs), termination (will a rule-based system produce an output at all) and response time (how much computation will a rule-based system have to do before it generates an output) can be difficult to predict These problems become even more challenging for distributed rule-based systems, where the system being designed or analysed consists of several communicating rule-based programs which exchange information via messages. This paper extends our previous work [32] and the main contributions of this paper are: first, to present an approach for the specification and verification of an ontology driven system that supports automated verification of time and communication requirements in distributed Semantic Web rule-based agents.
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