Guest Editors' Introduction: Rule Representation, Interchange, and Reasoning in Distributed, Heterogeneous Environments

IN recent years, rule-based technologies have enjoyed remarkable adoption in two areas: 1) business rule processing and 2) Web-centered reasoning. The first trend is caused by the software development life cycle, which needs to be accelerated at reduced cost. The second trend is related to the Semantic Web and Service-oriented technologies, which aim to turn the Web into a huge repository of cross-referenced, machine-understandable data and processes. For both trends, rules can be used to extract, derive, transform, and integrate information in a platform-independent manner. While early rule engines and environments were complex, expensive to maintain, and not very user friendly, the current generation of rule technology provides enhanced usability, scalability, and performance, and is less costly. A general advantage of using rules is that they are usually represented in a platform independent manner, often using XML. This fits well into today’s distributed, heterogeneous Web-based system environments. Rules represented in standardized Web formats can be discovered, interchanged, and invoked at runtime within and across Web systems, and can be interpreted and executed on any platform. This special section is focused on state-of-the-art approaches, solutions, and applications in the area of rule representation, reasoning, and interchange in the context of distributed, (partially) open, heterogeneous environments, such as the semantic Web, intelligent multiagent systems, event-driven architectures, and service-oriented computing. In response to the call for papers, we received a total of 52 submissions, out of which 7 were recommended submissions from the best ranked papers presented at the RuleML-2007 [1] and RuleML-2008 [2] “International RuleML Symposia on Rule Interchange and Applications” held in October 2007 and 2008, respectively, in Orlando, Florida. After careful and rigorous reviews, we have selected 8 papers, 3 of them being extended papers from RuleML Symposia, based on the quality and relevance of the papers. The first paper is ”Defeasible Contextual Reasoning with Arguments in Ambient Intelligence” by Antonis Bikakis and Grigoris Antoniou. It proposes a solution for contextual reasoning in ambient intelligence based on the multicontext systems paradigm, in which local context knowledge of ambient agents is encoded in rule theories (contexts), and information flow between agents is achieved through mapping rules that associate concepts used by different contexts. To handle imperfect contexts, multicontext systems have been extended with nonmonotonic features, local defeasible theories, defeasible mapping rules, and a preference ordering on the system contexts. On top of this, an argumentation framework and a distributed algorithm for query evaluation have been developed that exploit context and preference information to resolve potential conflicts. The second paper is “A Rule-Based Trust Negotiation System” by P.A. Bonatti, J.L. De Coi, D. Olmedilla, and L. Sauro. It presents PROTUNE, a rule-based Trust Negotiation (TN) framework. TN frameworks have been proposed as a better solution for open environments such as the Web, in which parties may get in touch and interact without being previously known to each other. PROTUNE offers certain advantages that arise from an advanced rulebased approach in terms of deployment efforts, user friendliness, communication efficiency, and interoperability. The generality and technological feasibility of PROTUNE’s approach are assessed through an extensive analysis and experimental evaluations. The third paper is “Efficient Lazy Evaluation of RuleBased Programs” by Peter Van Weert. It proposes a combination and cross-fertilization of the LEAPS production rule lazy matching algorithm (an extension to the Rete algorithm) with Constraint Handling Rules (CHR), a highlevel, declarative programming language, similar to production rules. While obviously related, CHR and production rules research have mostly evolved independently from each other. The paper provides a lucid, comprehensive overview of CHR’s rule evaluation methodology, and surveys recent contributions to the field of lazy matching. An empirical evaluation confirms that Rete-based engines would surely benefit from incorporating similar techniques and optimizations. The fourth paper is “A Configurable Rete-OO Engine for Reasoning with Different Types of Imperfect Information” IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 22, NO. 11, NOVEMBER 201