A Novel Approach to Distributed Sensory Networks Using Biologically-Inspired Sensory Fusion

A biologically inspired approach to sensory fusion and decision-making in a network of interacting autonomous agents is outlined. The underlying biological model (KIV) explores the hierarchy of dynamically interacting units, i.e., sensory cortices. Multi-sensory percept formation in vertebrates is used for modeling multi-agent cooperation in robot networks. Each agent autonomously performs its task, e.g., classification and pattern recognition. The autonomous units weakly interact to produce a coherent, goal-oriented behavior at the level of the overall network. High-level decision-making is manifested through the sequence of intermittent phase transitions in the network coordination unit, which is modeled based on the operation of the entorhinal cortex