Abstract
In order to handle complex situations, autonomous software agents need multiple components ranging from simple input/output modules to sophisticated AI techniques. Integrating a high number of heterogeneous components is a non-trivial task and this paper proposes the use of a symbolic middleware to handle inter-component interactions. A generalized hyper-graph model is defined, a simple and straightforward representation language is proposed and a pattern matching mechanism is introduced together with a basic performance evaluation. Finally, the paper shows how a flexible symbolic middleware can be built and a few examples are presented.
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Notes
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Dinu, R., Stratulat, T., Ferber, J. (2013). Intelligent Agents: Integrating Multiple Components Through a Symbolic Structure. In: Hatzilygeroudis, I., Palade, V. (eds) Combinations of Intelligent Methods and Applications. Smart Innovation, Systems and Technologies, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36651-2_1
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DOI: https://doi.org/10.1007/978-3-642-36651-2_1
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