A framework for constructing multi-agent applications and training intelligent agents
As agent-oriented paradigm is reaching a significant level of acceptance by software developers, there is a lack of integrated high-level abstraction tools for the design and development of agent-based applications. In an effort to mitigate this deficiency, we introduce Agent Academy, an integrated development framework, implemented itself as a multi-agent system, that supports, in a single tool, the design of agent behaviours and reusable agent types, the definition of ontologies, and the instantiation of single agents or multi-agent communities. In addition to these characteristics, our framework goes deeper into agents, by implementing a mechanism for embedding rule-based reasoning into them. We call this procedure ‘agent training’ and it is realized by the application of AI techniques for knowledge discovery on application-specific data, which may be available to the agent developer. In this respect, Agent Academy provides an easy-to-use facility that encourages the substitution of existing, traditionally developed applications by new ones, which follow the agent-orientation paradigm.
P. A. Mitkas, D. D. Kehagias, A. L. Symeonidis, I. N. Athanasiadis, A framework for constructing multi-agent applications and training intelligent agents, Agent-Oriented Software Engineering at Autonomous Agents and Multi-Agent Systems (AAMAS 2003), vol. W4, pg. 1-15, 2003.
You might also enjoy (View all publications)
- Storing, combining and analysing turkey experimental data in the Big Data era
- Enabling reusability of plant phenomic datasets with MIAPPE 1.1
- Defining and classifying infrastructural contestation: Towards a synergy between anthropology and data science