OVERVIEW EXAMPLE PRESENTATIONS PROBLEMS
& QUIZS
ERRATA LINKS
SW Vision
XML
RDF
OWL
Logic
Applications
Ontology Engineering
Conclusion




     Aditional Topics
Projects related to Chapter 5 - Logic
Project 5.1: Semantic Brokering
The aim is to implement an application similar to the apartment renting example in the book chapter.
Basic project (it should occupy 2 students for 2-3 weeks).
The following tasks should be carried out:
  • Select a topic in which a brokering activity is to be carried out. Here brokering refers to the matching of offerings and requirements.
  • Build at RDFS ontology for the domain.
  • Populate the ontology with offerings, expressed in RDF.
  • Express the selection criteria using nonmonotonic rules.
  • Run your rules with the RDF/RDFS information using an engine such as DR-DEVICE or DR-Prolog. To do so, you will need to express the rules in the format prescribed by these systems.
Advanced project (it should occupy 2-3 students for a term project).

The aim is to implement a brokering scenario in a multi-agent environment. Apart from carrying out the steps described in the basic project, project participants need, among others, to:

  • Develop a basic understanding of brokering in multi-agent environments by studying some relevant literature, e.g.

    K. Sycara, S. Widoff, M. Klusch, and J. Lu. Larks, Dynamic Matchmaking Among Heterogeneous Software Agents in Cyberspace, Autonomous Agents and Multi-Agent Systems 5, 2 (2002): 173-203 (pdf).

    G. Antoniou, T. Skylogiannis, A. Bikakis, and N. Bassiliades, A Deductive Semantic Brokering System, In Proc. 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems. LNCS 3682, Springer 2005, 746-752.
  • Choose and familiarize themselves with a multi-agent system. We have made good experience with JADE.
  • Decide on the precise messages to be exchanged between agents.
  • Find out how to call remotely the inference engine to be used.
Project 5.2: Proof Layer

The aim of this project is to realize a proof layer, the vision of which was briefly outlined in Chapter 1. A first remark is that there is not *the* proof layer, but rather a proof layer for each selected semantic web reasoning system (logic). Still, some considerations are common to all such systems.

Two possible logical systems for which one could implement a proof layer are:

  • A simple monotonic rules language, such as Datalog (Horn logic without function symbols). The reasoning tool Mandarax could be used.
  • A nonmonotonic rules language, as discussed in this chapter. DR-DEVICE or DR-Prolog could be used.
Basic project (it should occupy 2-3 students for 2 months).

The aim is to develop an interactive system that provides explanation to the user. Important aspects to be addressed include:

  • Decide how to extract relevant information from the overall proof trace. Project participants could consult the automated reasoning and logic programming literature for ideas.
  • Define levels of granularity for representing proofs. Should whole proofs be shown, or only meta-steps? These could then be refined if the user questions a certain step.
  • Ultimately, the "leaves" of a proof will be RDF facts, or rules, or inference conditions used.
Advanced project (it should occupy 3-4 students for a term project).

The aim is to implement a proof layer in a multi-agent environment.That is, requests and proof parts will be exchanged between agents. Additional aspects to be considered include:

  • Choose and familiarize themselves with a multi-agent system. We have made good experience with JADE.
  • Represent proofs in an XML language, ideally extending RuleML.
  • Decide on the precise messages to be exchanged between agents.




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