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Designing	
  systems	
  that	
  learn	
  
habitudes	
  of	
  interac5on	
  
November	
  6	
  2015	
  
Olivier.georgeon@lir...
Why	
  systems	
  should	
  learn	
  habitudes	
  
of	
  interac5on?	
  
•  Many	
  possible	
  applica5ons	
  	
  
–  Hum...
Demonstra5on	
  
3/9	
  liris.cnrs.fr/ideal	
  
Rudimentary distal perception
!"#$%!%
!"#$%&%
!"#$%'%
()*+$,%*#-*."/%0#,1%
Detects	
  rela5ve	
  displacement	
  	
  
of	
...
Self-­‐programming	
  
5/9	
  liris.cnrs.fr/ideal	
  
4.	
  Afford	
  
Time	
  
6.	
  Choose	
  
Decision	
  
Time	
  
3.	
  Ac5vate	
  
5.	
  Propose	
  
7.	
  Enact	
  
1.	
  ...
Eddie	
  robot	
  
7/9	
  liris.cnrs.fr/ideal	
  
Biologically	
  Inspired	
  Cogni5ve	
  Architecture	
  
h@p://e-­‐ernest.blogspot.com/	
  	
   8	
  
!"#$%&'()"*
+,-$.,"$...
Research/industry	
  collabora5on	
  	
  
•  Applica5ons	
  	
  
–  E.g.	
  Video	
  Games	
  (#Aimergence)	
  
•  Partner...
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Demo bica 2015

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Presentation at the research/industry meeting at BICA2015

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Demo bica 2015

  1. 1. Designing  systems  that  learn   habitudes  of  interac5on   November  6  2015   Olivier.georgeon@liris.cnrs.fr   h@p://liris.cnrs.fr/ideal   0 10 20 30 40 50 t   1/9  liris.cnrs.fr/ideal  
  2. 2. Why  systems  should  learn  habitudes   of  interac5on?   •  Many  possible  applica5ons     –  Human-­‐machine  interac.ons   •  Home  automa5on,  companion  robo5cs,  adap5ve  soJware   systems,  end-­‐user  programming,  etc.   •  Profound  theore5cal  reasons   –  Cogni.on  develops  by  sedimenta.on  of  habitudes   (David  Hume,    Edmund  Husserl,  Piaget,  etc.)   –  Leads  to  self-­‐programming:  crucial  to  intelligence.   –  Animal-­‐level  ar.ficial  intelligence   •  In  sharp  contrast  with  tradi5onal  AI  that  solves   predefined  problems  and  reach  predefined  goals.   liris.cnrs.fr/ideal   2/9  
  3. 3. Demonstra5on   3/9  liris.cnrs.fr/ideal  
  4. 4. Rudimentary distal perception !"#$%!% !"#$%&% !"#$%'% ()*+$,%*#-*."/%0#,1% Detects  rela5ve  displacement     of  objects  and  approximate  direc5on     within  180°  span  (area  A,  B,  or  C).     “Likes”  rapprochement.   “Dislikes”  disappearance.   4/9  liris.cnrs.fr/ideal  
  5. 5. Self-­‐programming   5/9  liris.cnrs.fr/ideal  
  6. 6. 4.  Afford   Time   6.  Choose   Decision   Time   3.  Ac5vate   5.  Propose   7.  Enact   1.   Trace-­‐Based  Reasoning   6/7  liris.cnrs.fr/ideal  
  7. 7. Eddie  robot   7/9  liris.cnrs.fr/ideal  
  8. 8. Biologically  Inspired  Cogni5ve  Architecture   h@p://e-­‐ernest.blogspot.com/     8   !"#$%&'()"* +,-$.,"$* /0)'$"#%,'*12&(&.** 3$-)%4* 5,$%&%'6,'&.*1$78$"(&.*3$-)%4* 9$6&:,)%** 1$.$'()"* !"#$";* <%)2)=$* <%)2)=$* >$&%"*?*+%&'@* A"#).)04* /:)@$* B)"=#%8'#* /"&'#* CD/E+*
  9. 9. Research/industry  collabora5on     •  Applica5ons     –  E.g.  Video  Games  (#Aimergence)   •  Partnerships  for  research  projects     –  (student  internships,  Research  grants,  etc.)   •  We  are  looking  for  jobs  !   •  Open  to  your  sugges5ons…   9/9  liris.cnrs.fr/ideal  

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