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    A Theory of Reflective Agent Evolution 

    Murdock, J. William (Georgia Institute of Technology, 1998)
    Intelligent agents typically operate in complex, dynamic environments. Such environments require that an agent be able to adapt to meet new demands. One promising strategy for such adaptation is to have an agent reason ...
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    Behavioral Diversity in Learning Robot Teams 

    Balch, Tucker (Georgia Institute of Technology, 1998)
    This work investigates the origins of behavioral diversity in learning robot teams. Behavioral diversity refers to the extent to which agents assume distinct behavioral roles in a group. Most research in multi-robot teams ...
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    AQUA: Questions that Drive the Explanation Process 

    Ram, Ashwin (Georgia Institute of Technology, 1993)
    In the doctoral dissertation from which this chapter is drawn, Ashwin Ram presented an alternative perspective on the processes of story understanding, explanation, and learning. The issues that Ram explores in that ...
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    Failure-driven learning as model-based self-redesign 

    Stroulia, Eleni (Georgia Institute of Technology, 1994)
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    Introspective multistrategy learning : constructing a learning strategy under reasoning failure 

    Cox, Michael Thomas (Georgia Institute of Technology, 1996-05)
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    Behavioral diversity in learning robot teams 

    Balch, Tucker (Georgia Institute of Technology, 1998)
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    Learning Roles: Behavioral Diversity in Robot Teams 

    Balch, Tucker (Georgia Institute of Technology, 1997)
    This paper describes research investigating behavioral specialization in learning robot teams. Each agent is provided a common set of skills (motor schema-based behavioral assemblages) from which it builds a task-achie ...
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    Learning Momentum: On-Line Performance Enhancement for Reactive Systems 

    Arkin, Ronald C.; Clark, Russell J.; Ram, Ashwin (Georgia Institute of Technology, 1992)
    We describe a reactive robotic control system which incorporates aspects of machine learning to improve the system's ability to successfully navigate in unfamiliar environments. This system overcomes limitations of completely ...

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    AuthorBalch, Tucker (3)Ram, Ashwin (2)Arkin, Ronald C. (1)Clark, Russell J. (1)Cox, Michael Thomas (1)Murdock, J. William (1)Stroulia, Eleni (1)Subject
    Machine learning (8)
    Artificial intelligence (5)Adaptation (2)Multi-robot teams (2)Adaptive control (1)AQUA (1)Autonomous navigation (1)Behavior based learning (1)Explanation patterns (1)Global reinforcement (1)... View MoreDate Issued1998 (3)1997 (1)1996 (1)1994 (1)1993 (1)1992 (1)
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