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
Sponsor: Electrical Engineering and Computer Science
Cosponsor: Engineering Systems Division
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
Latest update: 03-Jan-2005
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