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The volume aims at providing a comprehensive review of the diverse efforts covering the gap existing between the two main perspectives on the topic of ontologies for multi-agent systems, namely: How ontologies should be modelled and represented in order to be effectively used in agent systems, and on the other hand, what kind of capabilities should be exhibited by an agent in order to make use of ontological knowledge and to perform efficient reasoning with it. The volume collects the most significant papers of the AAMAS 2002 and AAMAS 2003 workshop on ontologies for agent systems, and the EKAW 2002 workshop on ontologies for multi-agent systems.
Zusammenfassung
There is a growing interest in the use of ontologies for multi-agent system app- cations. On the one hand, the agent paradigm is successfully employed in those applications where autonomous, loosely-coupled, heterogeneous, and distributed systems need to interoperate in order to achieve a common goal. On the other hand, ontologies have established themselves as a powerful tool to enable kno- edge sharing, and a growing number of applications have bene?ted from the use of ontologies as a means to achieve semantic interoperability among heterogeneous, distributed systems. In principle ontologies and agents are a match made in heaven, that has failed to happen. What makes a simple piece of software an agent is its ability to communicate in a ”social” environment, to make autonomous decisions, and to be proactive on behalf of its user. Communication ultimately depends on und- standing the goals, preferences, and constraints posed by the user. Autonomy is theabilitytoperformataskwithlittleornouserintervention,whileproactiveness involves acting autonomously with no need for user prompting. Communication, but also autonomy and proactiveness, depend on knowledge. The ability to c- municate depends on understanding the syntax (terms and structure) and the semantics of a language. Ontologies provide the terms used to describe a domain and the semantics associated with them. In addition, ontologies are often comp- mented by some logical rules that constrain the meaning assigned to the terms. These constraints are represented by inference rules that can be used by agents to perform the reasoning on which autonomy and proactiveness are based.
