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Symbolic Learning for Adaptive Agents (2003)  (Make Corrections)  (1 citation)
Joshua Cole The Australian National University Email: ...



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Abstract: This paper investigates an approach to designing and building adaptive agents. The main contribution is the use of a symbolic machine learning system for approximating the policy and Q functions that are at the heart of the agent. Under the assumption that sufficient knowledge of the application domain is available, it is shown how this knowledge can be provided to the agent in the form of symbolic hypothesis languages for the policy and Q functions, and the advantages of such an approach. A... (Update)

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BibTeX entry:   (Update)

J. Cole, J.W. Lloyd, and K.S. Ng. Symbolic Learning for Adaptive Agents. In Proc. Annual Partner Conference, Smart Internet Technology Cooperative Research Centre, 2003. http://csl.anu.edu.au/ jwl/crc paper.pdf http://citeseer.ist.psu.edu/cole03symbolic.html   More

@misc{ cole03symbolic,
  author = "J. Cole and J. Lloyd and K. Ng",
  title = "Symbolic Learning for Adaptive Agents",
  text = "J. Cole, J.W. Lloyd, and K.S. Ng. Symbolic Learning for Adaptive Agents.
    In Proc. Annual Partner Conference, Smart Internet Technology Cooperative
    Research Centre, 2003. http://csl.anu.edu.au/ jwl/crc paper.pdf",
  year = "2003",
  url = "citeseer.ist.psu.edu/cole03symbolic.html" }
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