Learning to Optimize Performance: Lessons from a Neural Control System

Abstract

Cognitive processes in human-machine interaction are mostly executed in the cerebral cortex (and other parts of the higher brain) which is designed for multi-tasking operations but is generally not optimized for any specific task. Similar cognitive and control operations also occur in the brain stem which is composed of many task specific neural modules for the homeostatic regulation of a host of physiological functions using peripheral processes as the “machine”. In the respiratory control system, the brain stem controller demonstrates intelligent control capability and achieves optimal performance under a wide variety of environmental conditions. Such intelligent control behavior can be realized by reinforcement learning in an associative Hebbian synapse in the brain stem. Similar reinforcement learning modules in the higher brain can be fashioned by repeated training to effect robust optimal operation in a human-machine system.