Ontologies for agents

Más información sobre el libro

There is a growing interest in using ontologies for multi-agent system applications. The agent paradigm effectively supports autonomous, loosely-coupled, heterogeneous, and distributed systems that need to collaborate to achieve common goals. Simultaneously, ontologies serve as a powerful tool for knowledge sharing, facilitating semantic interoperability among diverse systems. While ontologies and agents should ideally complement each other, this synergy has not fully materialized. An agent is defined by its ability to communicate in a social environment, make autonomous decisions, and act proactively for its user. Effective communication hinges on understanding user goals, preferences, and constraints. Autonomy allows an agent to perform tasks with minimal user intervention, while proactiveness involves taking initiative without user prompting. All these capabilities rely on knowledge. Communication necessitates an understanding of both the syntax (terms and structure) and semantics of a language. Ontologies provide the necessary terminology and associated semantics for a domain. Additionally, ontologies often include logical rules that define the meanings of terms, represented by inference rules that agents can use for reasoning, which underpins their autonomy and proactiveness.