Rule Responder: Rule-Based Agents for the Semantic-Pragmatic Web.

International Journal of Artificial Intelligence Tools (Impact Factor: 0.32). 12/2011; 20(6):1043-1081. DOI: 10.1142/S0218213011000528
Source: DBLP

ABSTRACT Rule Responder is a Pragmatic Web infrastructure for distributed rule-based event processing multi-agent eco-systems. This allows specifying virtual organizations -- with their shared and individual (semantic and pragmatic) contexts, decisions, and actions/events for rule-based collaboration between the distributed members. The (semi-)autonomous agents use rule engines and Semantic Web rules to describe and execute derivation and reaction logic which declaratively implements the organizational semiotics and the different distributed system/agent topologies with their negotiation/coordination mechanisms. They employ ontologies in their knowledge bases to represent semantic domain vocabularies, normative pragmatics and pragmatic context of event-based conversations and actions.

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    ABSTRACT: Rule Responder is a rule-based multi-agent framework in which agents run platform-specific rule engines as distributed inference services. They communicate with each other using Reaction RuleML as the common rule interchange format, e.g. for question answering or execution of mobile rule code in distributed problem solving, concurrent processing workflows and distributed event/action processing. In this paper we demonstrate the new capabilities of Reaction RuleML 1.0 for supporting the functionalities of Rule Responder such as knowledge interface declarations with signatures, modes, and scopes; distributed knowledge modules with static and dynamic scopes enabling imports and scoped reasoning within metadata-based scopes (closed constructive views) on the knowledge base; messaging reaction rules enabling conversation-scope based interactions between agents interchanging queries, answers, and rulebases; and evaluation and testing of interchanged knowledge bases with intended semantic profiles and self-validating test suites. We demonstrate these Reaction RuleML 1.0 capabilities with our proof-of-concept implementation Rule Responder agent architecture and Prova 3.0 rule engine.
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Jun 5, 2014