An architecture for robot intelligence enables a robot to learn new
behaviors and create new behavior sequences autonomously and interact with
a dynamically changing environment. Sensory information is mapped onto a
Sensory Ego-Sphere (SES) that rapidly identifies important changes in the
environment and functions much like short term memory. Behaviors are
stored in a DBAM that creates an active map from the robot's current state
to a goal state and functions much like long term memory. A dream state
converts recent activities stored in the SES and creates or modifies
behaviors in the DBAM.
