1. SIMULATIONS, REALIZATIONS, AND THEORIES OF LIFE H. H. PATTEE (1989) By Hyojung Seo Dept. of Psychology

2. CONTENTS How Universal is a Computer? Realizations, Simulations, and Theories The Limitations of Theory-free Simulations Simulations do not become Realizations The Symbol-Matter Problem Weak or Strong Artificial Evolution? Three Levels of Emergent Behavior Can we Artificially Evolve New Measurements? Conclusions

3. How would we distinguish computer simulations from realizations of life? How does this relate to theories of life? : how can the living be distinguished from the non-living? Hope of Strong AL: Langton (1987) ‘We would like to build models that are so lifelike that they would cease to be models of life and become examples of life themselves’ Needed Discussion

4. 1. Simulations and Realizations belong different categories of modeling. Simulations: metaphorical models that symbolically ‘stand for’ something else. Realizations: literal, material models that implement functions 2. The criteria for good simulations and realizations of a system depend on our theory of the system. 3. Our theory of living systems must include evolvability. evolution: symbolic genotypes, material phenotypes, selective environments Main Ideas

5. How Universal is a Computer? Artificial Life studies have closer roots in Artificial Intelligence and Computational modelling than in Biology itself. Platonic ideal & AI - rule-based formalists - law-based ecological realists - neural network, connectionist, & parallel distributed processor

6. How Universal is a Computer? (Cont’d) The criticism of AI, which will be aimed at AL as well, is that it has for the most part neglected the fundamental biology of the nervous system. Who decides ‘What is fundamental about biology’? : A theory of life must be decisive. neuroscientists: a model of the brain that is empirically testable in biological systems.

7. Realizations, Simulations, and Theories 1) Computer-dependent realizations of living systems 2) Computer simulations of living-systems behavior 3) Theories of life that derive from simulations 4) Theories of life that are testable only by computer simulations Need to distinguish between,

8. Realizations, Simulations, and Theories (Cont’d) Realization Judged by how well it can function as an implementation of a design specification The problem of AL is, What is the operation or function of living? The classical theory of life requires, symbolic genotype, material phenotype, environment

9. Two possibilities for strong AL: (1) include robotics to realize the phenotype-environment interactions (2) treat the symbolic domain of the computer as an artificial environment in which symbolic phenotype properties of artificial life are realized Realizations, Simulations, and Theories (Cont’d) Realization (cont’d)

10. Simulation Realizations, Simulations, and Theories (Cont’d) Judged by how well they generate similar morphologies or parallel behaviors. of some specified aspects of the system The simulation, no matter how accurate, is not the same as the thing simulated. : has extra features of simulation medium that are not found in the system The simulation depends on theory. : represents the essential functions of a realization of the system

11. Theories Realizations, Simulations, and Theories (Cont’d) Judged by abstract tests of universality, conceptual coherence, simplicity and elegance Judged by concrete tests of how well they can predict specific values for the observables of the system being modelled.

12. Physics: formal theoretical structures - mathematical models of generality and formal simplicity that do not have perceptual or behavioral similarities with the world they model The study of dynamical systems by computer often blurs the distinction between theories and simulations.

13. The Limitations of Theory-Free Simulations Computational Universality Newell & Simon, Physical Symbol System Hypothesis : Computation can realize intelligent thought. ‘This form of symbolic behavior is all there is; it includes human symbolic behavior.’ In AI The power of computer simulation obscures the basic requirements of a scientific theory.

14. The Limitations of Theory-Free Simulations (Cont’d) Problem : It has not been verified by the delicate criteria for theory; A working simulation is not really evidence for the theory. both simulations and realizations must be evaluated in terms of a theory of the brain, and the empirical evidence for that theory.

15. Simulations TheoryRealization Theory Simulations Realization

16. In AL The Limitations of Theory-Free Simulations (Cont’d) Working simulations are not by themselves evidence for or against theories of life. There are many alternative ways to successfully simulate any behavior. All the models must be evaluated by theory. We must allow only universal physical laws and the theory of natural selection to restrict the evolution of artificial life.

17. Simulations do not become Realizations Categorical difference: Realization: literal, substantial replacement Simulation: metaphorical representation of specific structure or behavior - symbolic forms, not material substance Measurement in Simulation: A mapping from observable aspects of the system to corresponding symbolic elements of the simulation

18. problem of formalization of life The Symbol-Matter Problem The molecular facts do not constitue a theory of how symbolic forms and material structures must interact to evolve. Need for the theory of evolution Von Neumann(1966) : evolution of complexity - the essential characteristic of life - symbolic instructions and universal construction necessary for heritable & open-ended evolution : the problem of the relation of symbol and matter

19. The Symbol-Matter Problem (Cont’d) The Physical Symbol System Hypothesis is half-truth: - We can construct symbol system from matter. - Matter can not be constructed from symbols. - Evolutionary Hypothesis: under the symbolic control of genotypes, material phenotypes in an environment can realize endless varieties of structures and behaviors.

20. (1) we can simulate everything by universal symbol systems (2) we can realize universal symbol systems with material constructions (3) we can realize endless types of structures and behaviors by symbolic constraints on matter The Symbol-Matter Problem (Cont’d) we cannot realize material systems with symbols alone Three symbol-matter possibilities: Fundamental impossibilities:

21. Weak or Strong Artificial Evolution AL realization should include the genotype, phenotype, environment distinctions as well as the corresponding mutability, heritability and natural selection of neo-Darwinian theory. A realization of life should have the emergent or novel evolutionary behavior that goes beyond adaptation to an environment.

22. Whether formal environment like a computer can realize evolutionary novelty or merely simulate? Computation / physical models - Computational universality and physical universality refer to different domains. physical theories: observable world. universality -- restrictions on theories computational universality: symbolic domain universality -- no restriction on symbolic rewriting rule Weak or Strong Artificial Evolution (Cont’d)

23. Three Levels of Emergent Behaviour Syntactic emergence: symmetry-breaking, chaotic dynamics strong emergence / weak emergence Semantic emergence non-dynamical symbol systems Measurement itself

24. Can we artificially evolve New Measurement? New measurements as one of the more fundamental test cases for emergent behavior in artificial life models. Generalized measurement is a record stored in the organism of some type of classification of the environment and this classification must be realized by a measuring device.

25. Can we artificially evolve New Measurement? The primary processes of evolution is the construction of new measuring devices, and this type of substantive emergence is out of the domain of symbolic emergence, so we cannot expect to realize this natural type of evolutionary emergence with computers alone. Autonomous classification: reclassification of the results of measurement, no new measurement :realization of semantic emergence

26. Conclusions 1. AL must evaluate its models by the strength of its theories of living systems, and not by technological mimicry alone. 2. There is nothing wrong with a good illusion as long as one does not claim it is reality. 3. AL should pay attention to the enormous knowledge base of biology. 4. The process of measurement is proposed as a test case for the distinction between simulation and realization