Modular Design Patterns for Hybrid Actors
This work provides a modular framework for researchers and practitioners in AI to design hybrid systems, but it is incremental as it builds on prior boxology concepts.
The paper tackles the problem of designing distributed hybrid AI systems by extending an existing graphical language (boxology) to include actors and their interactions, resulting in a taxonomy and examples for multi-agent systems and human-agent interaction.
Recently, a boxology (graphical language) with design patterns for hybrid AI was proposed, combining symbolic and sub-symbolic learning and reasoning. In this paper, we extend this boxology with actors and their interactions. The main contributions of this paper are: 1) an extension of the taxonomy to describe distributed hybrid AI systems with actors and interactions; and 2) showing examples using a few design patterns relevant in multi-agent systems and human-agent interaction.