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15-882A: CMU's Introduction to Artificial Neural Networks

This directory contains some of the materials for CMU's graduate course 15-882A, "Introduction to Artificial Neural Networks". Some materials have been excluded due to copyright restrictions (e.g., the PDP simulator). There is some software included with the handouts and syllabus: backprop.lisp A direct implementation of the backpropagation learning algorithm of Rumelhart, Hinton, and Williams, for networks with a single hidden layer. Written by David Touretzky, July 1991. backprop.c Backpropagation algorithm for training a fully-connected MLP neural network with 1 layer of hidden units. Ported to C from backprop.lisp by Justin Boyan, 5-OCT-93. perceptron.lisp A simple-minded simulator for two-input perceptrons. Written by David Touretzky, January 1990. perceptron.c A simple-minded simulator for 2 bool input to 1 bool output perceptrons. Ported to C from perceptron.lisp by Justin Boyan, September 1993. qpole.c Q-learning to solve the cart-pole problem. Written by Rich Sutton, Chuck Anderson, and Claude Sammut.

Version: Fall 1993 CD-ROM: Prime Time Freeware for AI, Issue 1-1 Author(s): Dave Touretzky, Alex Waibel, and Scott Fahlman (Instructors) Keywords: Authors!Anderson, Authors!Boyan, Authors!Sammut, Authors!Sutton, Authors!Touretzky, Backpropagation, Cart-Pole Problem, Connectionist Systems, Lecture Notes!Neural Networks, Machine Learning!Neural Networks, Neural Networks!Simulators, Neural Networks!Teaching Materials, Perceptrons, Problem Sets!Neural Networks, Q-Learning, Teaching Materials!Neural Networks References: ?
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