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

International Journal of Artificial Intelligence Tools (Impact Factor: 0.39). 12/2011; 20(6):1043-1081. DOI: 10.1142/S0218213011000528
Source: DBLP


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.

Download full-text


Available from: Adrian Paschke
  • Source
    • "Abstracting and associating services 1 with knowledge-empowered agents without changing these services implementation has already been proposed and widely analyzed (Garcia-Sancheza, Valencia-Gariaa, Martinez-Bejarb, & Fernandez-Breis, 2009; Lomuscio , Qu, & Solanki, 2012; Maamar, Moustefaoui, & Yahyaoui, 2005; Paschke & Boley, 2011; Pradhan & Lu, 2007). Such an agent-based abstraction benefits services from advanced interaction and decision-making techniques that those agents are able to manage (Jacyno , Bullock, Luck, & Payne, 2009; Bentahar, Khosravifar, Serhani, & Alishahi, 2012; Sanchez-Anguix, Valero, & Garcia-Fornes, 2011). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Frameworks for aggregating similar services into structures called communities have been recently advocated. A common assumption in those frameworks is that residing services are coopetitive, i.e., competing over received requests, but also cooperating, for instance in terms of substituting each other. In this coopetition context, deciding to compete or cooperate at different moments in time is an open question yet to be addressed. The contribution of this paper is the answer to this challenging question by proposing a game-theoretic-based decision mechanism that services can use to effectively choose competition or cooperation strategies that maximize their payoffs. To achieve this objective, we investigate autonomous services’ characteristics and their expected utilities over different strategies. We propose a game-theoretic best response technique to measure the threshold that services can use in order to decide about the two strategies. We prove that the proposed decision mechanism is efficient and can be implemented in time linear in the length of the time period considered for the analysis and the number of services in the community. Moreover, we conduct extensive simulations to analyze various scenarios and confirm the obtained theoretical results. Those results show that our model outperforms existing competitive and random coopetitive strategies and the more services deviate from our game-theoretic-based coopetitive strategy the more they make less benefits.
    Full-text · Article · Aug 2014 · Expert Systems with Applications
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The Internet is more than a web of computers and more than a web of documents. From a pragmatic point of view it is interesting what people do with the Internet and how. Actions and events have a meaning in the context of a process or practice as enveloping a set of shared norms. The norms apply to behavior, but also to interpretation and evaluation, and can be represented and implemented using rule-based systems.
    Full-text · Conference Paper · Jan 2012
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Reaction RuleML is one of the two major subfamilies of RuleML and acts as an interchange format for reactive rules and rule-based event-processing languages. Exemplified with a recent instantiation of Rule Responder, a rule-based inference agent middleware, we demonstrate the event messaging features of Reaction RuleML, which supports loosely-coupled interface-based interaction using rule signatures and decoupled communication via event messages.
    Full-text · Article · Aug 2012
Show more