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                Alife seminar: Evolvable Autonomous Agents
               --------------------------------------------
               --------------------------------------------


                    Eytan Ruppin (ruppin@math.tau.ac.il)
                     Semester bet, 2002
                      Thursday, 3-5 pm, Shenkar 222.

                        Summary:
                       -----------

 After a brief introduction to alife and genetic algorithms, we shall 
focus on the computational evolution of autonomous agents. More specifically, 
we shall concentrate on neural-network guided agents, and mainly on such 
software robots (``softbots'').  Our goal is to get a feeling of what can
be currently achieved with such agents, that is, what tasks can they perform
and what can be learned by using them as a computational neuroscience 
research tool. 

                      Technicalities:
                    ------------------

 Enclosed below is the list of articles to be presented and discussed
in the seminar. They are listed in the order they should be presented,
with some possible leeway. 

 General guidelines for your presentations in the seminar include:

       1. Make sure you understand the theme of your talk thoroughly, 
        and are versed with the background, motivation, research questions,
       methodology and results.

       2. Prepare and deliver a clear presentation - have slides with 
       little text as possible, rehearse your presentation a few times to
       make sure you're fluent with it and can deliver it within the
      allotted time limits (45 minutes), which will be strictly enforced.
       Prepare for possible and likely questions.
            
       3. Prepare a 2-3 page summary of the main ideas conveyed in your
         talk (the more concise, the better..), to be email-ed to me
        after your talk.


                   Program and Article Selection
                ------------------------------------


             A. Introduction -  Alife:
            ---------------------------

          Talk 1.   General Introduction to brains, genes and evolution
          - Eytan Ruppin

          Talk 2.   Genetic algorithms and Artificial life - 
         Eytan Ruppin

         
             B. Introductory papers:
           ------------------------------


         1.  Theoretical Foundations of Genetic Algorithms
               (Chapter 4, Mitchell's book)
         
         2.  Theoretical Foundations of  Alife
               (Chapter 4, Fogel's book)

         3.   An evolutionary approach to synthetic biology:
              Zen and the art of creating life, by Thomas Ray   
              (In Artificial Life, Chris Langton, 1995, and a pointer to
             his web site can be found at 
              http://lslwww.epfl.ch/~moshes/caslinks.html)
             --  Igor B (igorb@post)

         4. V.~Braitenberg.
            \newblock {\em Vehicles, Experiments in Synthetic Psychology}.
            \newblock MIT Press, Cambridge MA, 1984.
             --  Eran Werner (ewerner@idc.ac.il).           

            C. Main Seminar Theme: EAAs and Neuroscience 
         -------------------------------------------------

        5.  Evolutionary Neurocontrollers for Autonomous Mobile Robots,
D. Floreano and F. Mondada, Neural Networks, 1461-1478, 1998.

        6. J.~Kodjabachian and J.A. Meyer.
\newblock Evolution and development of neural controllers for locomotion,
  gradient-following and obstacle-avoidance in artificial insects.
\newblock {\em IEEE Transactions on Neural Networks}, 9(5):796--812, 1998.

        7. C.~Scheier, R.~Pfeifer, and Y.~Kunyioshi.
\newblock Embedded neural networks: Exploiting constraints.
\newblock {\em Neural Networks}, (7-8):1551--1569, 1998.
       -- Amit Levy (a_r_levy@hotmail.co.il)

        8. Evolution of homing navigation in a real mobile robot,
Dario Floreano and Francesco Mondada 
(IEEE Trans. Sys. Man. Cyber., 26(3), 396-407, 1996) -
        --  Ophir Gvirter (ophirgv@hotmail.com)

        9. Incremental evolution of complex general behavior,
Faustino Gomez and Risto Mikkulainen
(Adaptive behavior, 5(3/4), 317-342, 1997) 

        10. Using Emergent Modularity to Develop Control Systems for 
Mobile Robots, Stefano Nolfi 
(Adaptive behavior, 5(3/4), 365-390, 1997) 
        -- Rotem Peles ( pelesrot@post )

        11. Y.~Niv, D.~Joel, I.~Meilijson, and E.~Ruppin.
\newblock Evolution of reinforcement learning in foraging bees in neural terms.
\newblock In {\em Tenth Annual Computational Neuroscience Meeting (CNS2001)}.
  2001.

        12. I.~Harvey, P.~Husbands, and D.~Cliff.
\newblock Seeing the light: Artificial evolution, real vision.
\newblock In D.~Cliff, P.~Husbands, J.A. Meyer, and S.~Wilson, editors, {\em
  From Animals to Animats 3, Proc. of 3rd Intl. Conf. on Simulation of Adaptive
  Behavior, SAB94}. MIT Press/Bradford Books, 1994.
        - Zohar Ganon (ganonzoh@post)

        13. A.J. Ijspeert and J.~Hallam amd D.~Willshaw.
\newblock Evolving swimming controllers for a simulated lamprey with
  inspiration from neurobiology.
\newblock {\em Adaptive Bahvior}, 7:151--172, 1999.
        - Yishai Eliada (yishai@eliada.com)

        14. R.~Aharonov-Barki, T.~Beker, and E.~Ruppin.
\newblock Emergence of memory-driven command neurons in evolved artificial
  agents.  \newblock {\em Neural Computation}, (13):691--716, 2001.
     -- Ben Sandback (ptaph@netvision.net.il)

        15. P.~Husbands, T.~Smith, N.~Jacobi, and M.~Oshea.
\newblock Better living through chemestry: Evolving {G}as{N}ets for robot
  control.  \newblock {\em Connection Science}, 10:185--210, 1998.
     --  Eran Polosetski ( eranpolo@hotmail.com )

        16. S.~Nolfi and D.~Floreano.
\newblock Learning and evolution.
\newblock {\em Autonomous Robots}, (7):89--113, 1999.
      -- Roi Yehoshua (yehoshu@post)

        17. E.T. Rolls and S.M. Stringer.
\newblock On the design of neural networks in the brain by genetic algorithms.
\newblock {\em Progress in Neurobiology}, (61):557--579, 2000.
        -- Ori (orie@tcc.huji.ac.il)
       

        18.   D.~Floreano and J.~Urzelai.
\newblock Evolutionary robots with online self-organization and behavioral
  fitness.  \newblock {\em Neural Networks}, (13):431--443, 2000.
        - Ofer  Molad (o_molad@hotmail.com )