A mathematical framework for the study of learning in a variety of domains. Systems That Learn presents a mathematical framework for the study of learning in a variety of domains. It provides the basic concepts and techniques of learning theory as well as a comprehensive account of what is currently known about a variety of learning paradigms.
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" This is highly original and interesting research. "Systems That Learn" is an important addition to human knowledge and an incipient classic." -- Steven Pinker, MIT
" "Systems That Learn" is a book that has much to offer... Osherson, Stob, and Weinstein provide an interesting contrast to most of the learning work done either in psychology or artificial intelligence." -- "Contemporary Psychology"
& quot; This is highly original and interesting research. Systems That Learn is an important addition to human knowledge and an incipient classic.& quot; -- Steven Pinker, MIT
& quot; Systems That Learn is a book that has much to offer... Osherson, Stob, and Weinstein provide an interesting contrast to most of the learning work done either in psychology or artificial intelligence.& quot; -- Contemporary Psychology
"
""Systems That Learn" is a book that has much to offer... Osherson, Stob, and Weinstein provide an interesting contrast to most of the learning work done either in psychology or artificial intelligence."--"Contemporary Psychology"
"This is highly original and interesting research. "Systems That Learn" is an important addition to human knowledge and an incipient classic."--Steven Pinker, MIT
Daniel N. Osherson is at MIT. Michael Stob at Calvin College. Scott Weinstein is at MIT. Jeffrey Rosenschein is the Sam and Will Strauss Professor of Computer Science at the Hebrew University of Jerusalem.
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