On rationality and learning
نویسنده
چکیده
Much work in machine learning views learning primarily as a process of representation. We propose instead to view learning as the rational interpretation of experience. This provides a unifying, precise framework that illuminates both the strengths and weaknesses of current learning methods and the possibilities for uniformly mechanizing different types of learning. This research was supported by the Defense Advanced Research Projects Agency (DOD), ARPA Order No. 4976, Amendment 19, monitored by the Air Force Avionics Laboratory under Contract F33615-87-C-1499. The views and conclusions contained in this document are those of the author, and should not be interpreted as representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the Government of the United States of America.
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