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.
