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Artificial life

Artificial life. Based on Luc Steels (1995). Subject. Study : research and synthesis towards the artificial life domain Context : limits of system expert growth of computer power cognition approach. Start point.

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Artificial life

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  1. Artificial life Based on Luc Steels (1995)

  2. Subject • Study : • research and synthesis towards the artificial life domain • Context : • limits of system expert • growth of computer power • cognition approach

  3. Start point • Scientific article :« The Homo Cyber Sapiens, the Robot Homonidus Intelligens, and the ‘artificial life’ approach to artificial intelligence » Luc Steels (1995)

  4. Luc Steels • Specialized in the domain of artificial intelligence and artificial life applied to robot architectures and to the study of language Fig 1.Luc Steels

  5. Luc Steels’ background • Studied computer science at MIT (Massachusetts Institute of Technology – USA) • Director of Sony Computer Science Laboratory in Paris • Professor computer science at the University of Brussels • Founded the VUB AI Laboratory (1983) • Reviewer at CNRS

  6. Bionic man ? Intelligentsystems Artificial life Once upon a time… evolution Homo Erectus Homo Sapiens Us After us ?

  7. Axes of discussion • Bionic man or Homo cyber sapiens • Intelligent systems or Robot Homonidus Intelligens • Artificial life

  8. Artificial Life Bionic man or Homo Cyber Sapiens

  9. Homo Cyber Sapiens • Intelligence evolving towards greater : • sophistication • power • Homo Cyber Sapiens↔technological extensions of the human brain.

  10. Homo Cyber Sapiens • Artificial brain extensions should mimic the operation of human neurophysiology. • Neural modeling is implemented in chips • Artificial brain may be completely different from natural brain. • The build of bridges will establish data communication and processing.

  11. History • Brief History of Homo Cyber Sapiens/Post Humans. • Mary Shelley : Frankenstein (1831) • K.Eric Drexler (1980-1990) : Nanotechnology

  12. Evolution of Super Computer • Brain versus Super Computers • Ian Pearson, Chris Winter & Peter Cochrane (1995) Fig.1Projection of supercomputer speed

  13. Use Case • Two Examples :

  14. Artificial Life Intelligent Systems or Robot Homonidus Intelligens

  15. Intelligent systems • Cybernetic and Artificial Intelligence : already 50 years of experiment • Many advantages for computer science • A whole range of programs exhibit features of human intelligence • But …

  16. Limits of Intelligent systems • Steels : 3strong limits of Intelligent systems • a ‘frozen intelligence’ and not an intelligent behavior • intelligence needs to be embodied • consciousness

  17. First limit : frozen intelligence • Expensive cost of construction • Ephemeral validity • Outdated by changes • Expensive and unrealistic maintenance Something more than knowledge needed to be intelligent

  18. Second limit : lack of embodiment • Knowledge systems : • disembodied intelligence • no direct link to the real world • Intelligent behavior emerges from interactions • Difficulties : • link between the real world and the system symbols • adaptation to unforeseen actions

  19. Third limit : consciousness • An intelligent system needs a sense of self and a conscience • Possible ? • Existence of a true autonomous agent ?

  20. State of research in 1995 • No technological obstacle • The real obstacle :the lack of a theory of intelligence

  21. Fig 1. A robot soccer team by Nikos Vlassis (Amsterdam) State of research in 2005 (1/2) • Knowledge systems : example of ‘frozen intelligence’ • Case Based Reasoning use the last experience • Multi-agent systems : • agents • environment • interactions

  22. State of research in 2005 (2/2) • McCarthy (1995-2002) : • consciousness does not yet exist in intelligent system Intelligent systems emotions consciousness sub consciousness introspection

  23. Artificial Life The Artificial life approach : Theoretical approach

  24. 2005 Christopher Langton 1987 first scientific conference devoted to A-life Connectionism 1980 parallel, distributed processing, neural networksAI ↔ cognitive science 1970 John Conway game of life : simple system →complex self-organized structures Alan Turing 1948 “ ‘Intelligent machinery’ , It’s the birth of the concept of intelligent machines.” cellular automat John Von Neumann 1940 Historic (1/2)

  25. Historic (2/2) • Game of life : illustration Fig 1. Random start Fig 2. Stable state

  26. Definitions of A-life (1/2) • Langton (1989) : • Artificial life (A-life) : study of ‘natural’ life by attempting to recreate biological phenomena from scratch within computers and other ‘artificial’ media. • Rennard (2002) : • Life : state of what is not inert. • Artificial life : field of research witch intend to specify the preceding definition.

  27. Definitions of A-life (2/2) • Doyne Farmer and d'A.Belin (1992) : A-Life as field of alive • An artificial life must : • be initiated by man • be autonomous • be in interaction with its environment • induce the emergence of behaviors • Optional : • capacity to reproduce • capacities of adaptation

  28. Steels’ vision of A-life • Dynamic system theory applied to Artificial Intelligence • A-life →Unified theory of cognition • Unified theory : explain the details of all mechanisms of all problems within some domain. • unified theory of cognition domain’s ↔all cognitive behavior of humans. • experimental psychology could support such theories. (Newell 1990)

  29. Steels’ research path • Two kinds of behavior expected : • differentiation : individual agent get specific task • recognition : make the difference between the member of the group and those which don’t.recognition →emergence of language.

  30. Axes of research (1/2) • Emergence of language (Steels & Kaplan) • Emergence of common sense • Adaptation to other agents

  31. Axes of research (2/2) • Autonomous robotic (Floreano) • Genetic algorithms with neural networks • Co-evolution • Animat Approach (Meyer) • Synthesizing animal intelligence • Situated and incarnate cognition

  32. Artificial Life The Artificial life approach : Experimental approach

  33. Steels’ experimentation – 1995 (1/4) • A complete artificial ecosystem • An environment with different pressures for the robots • Robots are required to do some work which is paid in energy • Cooperation and competition with each other • Behavior systems

  34. Steels’ experimentation – 1995 (2/4) Fig 1. The ecosystem with the charging station, a robot vehicle, and a competitor Fig 2.A robot vehicle

  35. Steels’ experimentation – 1995 (3/4) Behavior system • Finding resources • Exploring Environment Perception - Visual Perception Modules Charging station, Competitors, Other robots - Sensors Light, Tactile • Obstacle avoidance • - Align on charging station • Align on competitors - Turn left/right, Forward, Retract, Stop - Motors

  36. Steels’ experimentation – 1995 (4/4) • Interesting results : • Behavior diversification • Hard working gourp • Lazy group • Steels : something could emerge from the lazy group

  37. Steel’s experimentation – 2001 (1/3) • One speaker (S), one hearer (H) • H tries to guess what S is talking about • H guess wrong : correction (feedback) • No explicit object designation : simple region pointing

  38. Steel’s experimentation – 2001 (2/3) Fig 3. The talking heads experiment

  39. Steel’s experimentation – 2001 (3/3) • Interesting results : • Emergence of a shared word • Winner-take-all • Shared word repertoires after experiment

  40. Other kind of experimentation (1/2) Floreano & al. (2004) • Evolution of Spiking Neural Networks in robots • Objective : Vision-based navigation and wall avoidance Fig 4. A Khepera robot in a square arena Fig 5.A Khepera robot

  41. Other kind of experimentation (2/2) • Interesting results : • Avoiding walls following with security distance • Biologically plausible connection patterns • Forward progression • Self adaptable speed : body adaptation

  42. Artificial Life Conclusion

  43. Conclusion (1/3) • 3 approaches • Bionic man : ethic problems • Intelligent systems : limits • Artificial life : • Tremendous possibilities • Involving many fields, biologically-inspired • Now a days the biological approach stay in progress.

  44. Conclusion (2/3) • Lack of intelligence theory • Problem of consciousness in robots • Is language needed for intelligence ? • Sufficient pressures for a new species ? • Does performance gain means Intelligence gain ?

  45. Conclusion (3/3) “Intelligence is like life or cosmos; its such a deep phenomenon that we will still be trying to understand it many centuries from now.” Luc Steels

  46. Homo Cyber Sapiens • The Anatomical changes are defined by : Homo erectus New sensory modalities. Homo Sapiens “wise man" • The Extreme ecological pressures are defined by: Homo erectus Homo Sapiens “wise man"

  47. Homo Cyber Sapiens • The human species is today under just as much stress as it must have been in the past,Still Human Intelligence haven’t evolved ! • How realistic is the development of a Homo Cyber Sapiens?

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