Algorithm Probability and Artificial Intelligence
Ray Solomonoff
No enrollment limit, no advance sign up
Participants welcome at individual sessions (series)
The lectures will be about an hour followed by questions and discussion. See below for information on individual sessions. Lecture notes and references will appear at the website below.
Web: http://world.std.com/~rjs
Contact: G. J. Sussman, gjs@mit.edu
Cosponsor: Electrical Engineering and Computer Science
Lecture 1: Algorithmic Probability
Ray Solomonoff
Algorithmic Probability - definitions and properties. How it is
related to MDL, stochastic complexity and Kolomogorov complexity. How to deal with its subjectivity and incomputability.
Wed Jan 12, 07-10:00pm, 32-144
Lecture 2: Applications of Algorithmic Probability
Ray Solomonoff
Linear and nonliner prediction. Neural nets and
genetic programming.
Wed Jan 19, 07-10:00pm, 32-144
Lecture 3: General Systems for Strong Artificial Intelligence
Ray Solomonoff
A definition for Strong Artificial Intelligence. Training
sequences. The role of Levin's Search Algorithm and enhanced
genetic programming in preliminary and advanced artificial
intelligence systems.
Wed Jan 26, 07-10:00pm, 32-144
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How to Design a Process
Michael Hammer
Tue Jan 25, Wed Jan 26, Thu Jan 27, 03-05:00pm, 56-114
No enrollment limit, no advance sign up
How is it possible to reduce cycle time (by as much as 80%), lower costs (by 50% or more), and improve quality and customer satisfaction -- all at the same time? What are the degrees of freedom available to a process designer? Where did Adam Smith, Henry Ford, and Frederick Taylor go wrong? How is a process like an engineering system? And what is a process anyway? Come to this three-part seminar and find out.
Michael Hammer is a Visiting Professor in ESD and is a former Associate Professor of Computer Science. He has written and taught extensively on process design and management, enterprise design, and change implementation.
Contact: Eda Daniel, E40-249, x3-1182, eda@mit.edu
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Understanding Appropriate Referencing Techniques and the Reality of Plagiarism
Patricia Brennecke, Lecturer in English Language Studies
Mon Jan 24, 02-03:30pm, E51-057
No enrollment limit, no advance sign up
Single session event
This 1-1/2 hour workshop will present strategies for avoiding plagiarism in academic writing. Exercises in quoting, paraphrasing, and documenting print and electronic sources will provide students with hands-on practice. Varieties of documentation styles (MLA, APA, etc.) will also be presented. This workshop is open to all graduate students but designed specifically for TPP/TMP and the greater ESD community.
Contact: Christine Ng, chrisng@mit.edu
Cosponsor: Technology and Policy Program
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