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Evolution of Artificial Life: Luc Steels' Insights (1995)

Explore the groundbreaking work of Luc Steels on artificial life evolution and robotic intelligence. From early concepts to current challenges, delve into the future of intelligent systems.

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Evolution of Artificial Life: Luc Steels' Insights (1995)

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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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