Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization

This volume is intended to help advance the field of artificial neural networks along the lines of complexity present in animal brains. In particular, we are interested in examining the biological phenomena of modularity and specialized learning. These topics are already the subject of research in another area of artificial intelligence. The design of complete autonomous agents (CAA), such as mobile robots or virtual reality characters, has been dominated by modular architectures and context-driven action selection and learning. In this chapter, we help bridge the gap from neuroscience to artificial neural networks (ANN) by incorporating CAA. We do this both directly, by using CAA as a metaphor to consider requirements for ANN, and indirectly, by using CAA research to better understand and model neuroscience. We discuss the strengths and the limitations of these forms of modeling, and propose as future work extensions to CAA inspired by neuroscience.

• Type: Conference
• Year: 2001
• Where: NEUROSCIENCE
• Authors: Joanna Bryson, Lynn Andrea Stein
• Keywords: Applied Computing, Artificial Neural Networks, Complete Autonomous Agents, NEUROSCIENCE 2001, Virtual Reality Characters