a rule-based system whose rules (termed productions) consist of two parts: a sensory precondition (or “if” statement) and an action (or “then”). If a production’s precondition (left-hand side or LHS) matches the current state of the world, then the production is said to be triggered. If a production’s action is executed, it is said to have fired. The rule interpreter must provide a mechanism for prioritizing productions when more than one is triggered. Rule interpreters generally execute a forward chaining algorithm for selecting productions to execute.
Published in Chapter:
Rule Engines and Agent-Based Systems
Agostino Poggi (Università di Parma, Italy) and Michele Tomaiuolo (Università di Parma, Italy)
Copyright: © 2009
|Pages: 7
DOI: 10.4018/978-1-59904-849-9.ch206
Abstract
Expert systems are successfully applied to a number of domains. Often built on generic rule-based systems, they can also exploit optimized algorithms. On the other side, being based on loosely coupled components and peer to peer infrastructures for asynchronous messaging, multi-agent systems allow code mobility, adaptability, easy of deployment and reconfiguration, thus fitting distributed and dynamic environments. Also, they have good support for domain specific ontologies, an important feature when modelling human experts’ knowledge. The possibility of obtaining the best features of both technologies is concretely demonstrated by the integration of JBoss Rules, a rule engine efficiently implementing the Rete-OO algorithm, into JADE, a FIPA-compliant multi-agent system.