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.


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    Title :

    Architecture for robot intelligence


    Contributors:

    Publication date :

    2004-02-24


    Type of media :

    Miscellaneous


    Type of material :

    No indication


    Language :

    English




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