Matchmaking for information agents

Abstract

The Internet not only provides data for users to browse, but also databases to query, and software agents to run. Due to the exponential increase of deployed agents on the Internet, automating the search and selection of relevant agents is essential for both users and collaboration among different software agents. This thesis research first describes the agent capability description language LARKS. Then the thesis presents an implementation language LARKS. The research did implement the language LARKS, the matchmaking process using LARKS, checking concept subsumption, computing concept distance in Java and XML.

Furthermore, the thesis discuses the research area on concept languages. A concept language is a part from Terminological Knowledge Representation systems, it is characterized by a set of operators that can be used to define complex concepts and roles. A concept describes a set of elements in the domain, and is defined by the conditions that must be satisfied by elements in the set. Several knowledge representation and inference systems, like ITL, CLASSIC, LOOM or KRIS, based on such languages are available.