Practical Reasoning Approaches for Web Ontologies and Multi-Agent Systems

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Logical and automated reasoning methods are crucial for web technologies and agent technologies for the intelligent processing of large ontologies, decision making based on knowledge bases of structured data, and formal specification and verification of multi-agent systems.Concerning ontology reasoning the current tableau description logic reasoners used for this purpose have a number of significant shortcomings. These include insufficient expressiveness, suboptimal complexity, over specialisation and incomplete formal treatment. All these are serious issues which need to be tackled and overcome if such systems are to form the backbone ontology reasoning for the semantic web. Concerning reasoning within and about multi-agent systems, in the form of intelligent decision making by agent and the formal specification and verification of agent systems, there exists a plethora of agent logics which have been proposed for this purpose, but almost no implemented reasoning systems for solving satisfiability and validity problems in these logics. This lack of system support is a serious problem.We will use techniques from first-order logic and resolution to develop a resolution framework for reasoning about expressive ontological languages and expressive agent logics. A series of tools will be developed to provide automated support for reasoning tasks in these areas. Principles of benchmarking will be studied, designed and used for empirical investigations of developed technologies and tools.