2 book chapters

[Juergen Schmidhuber]

        REINFORCEMENT LEARNING WITH SELF-MODIFYING POLICIES      

  Juergen Schmidhuber & Jieyu Zhao & Nicol N. Schraudolph (IDSIA)
  In S. Thrun and L. Pratt, eds., Learning to learn, Kluwer, 1997

We apply the success-story algorithm to a reinforcement learner whose 
learning algorithm  has modifiable components represented  as part of 
its own policy.   This is of interest in situations where the initial 
learning algorithm can be improved by experience (learning to learn).   
The system  is tested in a  complex partially observable environment.

                             ftp://ftp.idsia.ch/pub/juergen/ssa.ps.gz

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  A COMPUTER SCIENTIST'S VIEW OF LIFE, THE UNIVERSE, AND EVERYTHING

                     Juergen Schmidhuber (IDSIA)                 
  In C. Freksa,  ed.,  Foundations of Computer Science: Potential - 
  Theory - Cognition,  Lecture Notes in Comp. Sci., Springer, 1997.

Is the universe computable? If so, it may be much cheaper in terms of
information requirements  to compute all computable universes instead
of just ours.  I apply basic concepts of Kolmogorov complexity theory
to the set of possible  universes,  and chat about perceived and true
randomness,  life,  generalization,  and learning in a given universe.

                      ftp://ftp.idsia.ch/pub/juergen/everything.ps.gz

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