A biologically inspired action selection algorithm based on principles of neuromodulation

Abstract

The brain's neuromodulatory systems play a key role in regulating decision-making and responding to environmental challenges. Attending to the appropriate sensory signal, filtering out noise, changing moods, and selecting behavior are all influenced by these systems. We introduce a neural network for action selection that is based on principles of neuromodulatory systems. The algorithm, which was tested on an autonomous robot, demonstrates valuable features such as fluid switching of behavior, gating in important sensory events, and separating signal from noise.