How Far Can We Go Through Social System?

Situngkir, Hokky (2004) How Far Can We Go Through Social System? [Departmental Technical Report] (In Press)

Full text available as:



The paper elaborates an endeavor on applying the algorithmic information-theoretic computational complexity to meta-social-sciences. It is motivated by the effort on seeking the impact of the well-known incompleteness theorem to the scientific methodology approaching social phenomena. The paper uses the binary string as the model of social phenomena to gain understanding on some problems faced in the philosophy of social sciences or some traps in sociological theories. The paper ends on showing the great opportunity in recent social researches and some boundaries that limit them.

Item Type:Departmental Technical Report
Keywords:meta-sociology, algorithmic information theory, incompleteness theorem, sociological theory, sociological methods
Subjects:Computer Science > Language
Linguistics > Semantics
JOURNALS > Psycoloquy
Computer Science > Complexity Theory
Psychology > Psychophysics
Psychology > Psycholinguistics
Philosophy > Philosophy of Mind
Philosophy > Logic
JOURNALS > Behavioral & Brain Sciences
Psychology > Social Psychology
Philosophy > Philosophy of Language
Psychology > Cognitive Psychology
Computer Science > Artificial Intelligence
Philosophy > Epistemology
ID Code:3850
Deposited By: Situngkir, Mr Hokky
Deposited On:06 Oct 2004
Last Modified:11 Mar 2011 08:55

References in Article

Select the SEEK icon to attempt to find the referenced article. If it does not appear to be in cogprints you will be forwarded to the paracite service. Poorly formated references will probably not work.

1. Axtell, Robert. (2000). Why Agents? On the varied Motivations for Agent Computing in The Social Sciences. Working Paper No.17 Center on Social Economics Dynamics. The Brookings Institution.

2. Chaitin, G. (1974). "Information Theoretic Computational Complexity". IEEE Transactions on Information Theory IT-20:10-15.

3. Chaitin, G. (1975). "Randomness and Mathematical Proof". Scientific American 232(5):47-52.

4. Chaitin, G. (2004). Metamath!: The Quest for Omega. On-line publication. URL:

5. Coleman, J.S. (1990). Foundations of Social Theory. Harvard UP.

6. Collins, R. (1998). "The Sociological Eye and Its Blinders". Contemporary Sociology 27(1):2-7. American Sociological Association.

7. Craib, Ian. (1992). Modern Social Theory: From Parsons to Habermas 2nd ed. Harvester Wheatsheaf.

8. Doran, Jim. (1997). From Computer Simulation to Artificial Societies. Department of Computer Science. Essex University.

9. Durkheim, Emile (1895), Les Régles de la Méthode Sociologique, republished as The Rules of Sociological Method, The Free Press, 1965.

10. Edmonds, Bruce. (1999). Syntactic Measures of Complexity, PhD thesis. Faculty of Arts. University of Manchester. URL:

11. Epstein, J.M. & Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. The Brookings Institution Press & MIT Press.

12. Gilbert, N. & Troitzsch, K.G. (1998). Simulation for the Social Scientist. The Open University Press.

13. LaForte, G., Hayes, P.J., Ford, K.M. (1998). "Why Gödel's Theorem cannot refute Computationalism". Artificial Intelligence 104:265-86. Elsevier Science.

14. Langton, J. S. (2002). Artificial Societies and the Social Sciences. Working Paper WP 02-03-011. Santa Fe Institute.

15. Macy, M.W. & Willer, R. (2002). "From Factor to Actors: Computational Sociology and Agent-Based Modeling". Annual Review on Sociology 28:143-66.

16. Markose, S. M. (2002). "The New Evolutionary Computational Paradigm of Complex Adaptive Systems: Challenges and Prospects for Economics and Finance". in Chen, Shu-Heng (eds.). Genetic Algorithms and Genetic Programming in Computational Finance. pp.443-84. Kluwer Academic Publisher.

17. Martin, J. C. (1991). Introduction to Languages and the Theory of Computation. McGraw-Hill.

18. Merton, R. K. (1945). "Sociological Theory". The American Journal of Sociology 50(6):462-473. The University of Chicago Press.

19. Merton, R.K. (1968). Social Theory and Social Structure enl. ed. Free Press.

20. Nagel, E. & Newman, J.R. (2001). Gödel's Proof rev. ed. New York University Press.

21. Parsons, T. (1951). The Social System. Free Press.

22. Pattee, H.H. (1995). "Artificial Life Needs a Real Epistemology". in Moran, F., Moreno, A., Morelo, J.J., & Chacon, P. (eds.). Advances in Artificial Life pp. 23-38. Springer-Verlag.

23. Penrose, R. (1994). Shadows of the Mind: A Search for the Missing Science of Consciousness. Oxford UP.

24. Solomonoff, R. (1975). "Inductive Inference Theory - A Unified Approach to Problems in Pattern Recognition and Artificial Intelligence". Proceedings of the Fourth International Joint Conference on Artificial Intelligence, Tbilisi, Georgia, U.S.S.R. pp. 274-280.

25. Situngkir, Hokky. (2003). "Emerging the Emergence Sociology: The Philosophical Framework of Agent-Based Social Studies", Journal of Social Complexity 1(2): 3-15. Bandung Fe Institute.

26. Situngkir, Hokky. (2004). Jalan Panjang Menuju Sosiologi Komputasional: Sebuah Tutorial. On-line publication. URL:

27. Suber, P. (1998). "A Crash Course in the Mathematics of Infinite Sets". St. John's Review XLIV(2):35-59. URL:

28. Sullins, J.P. III (1997). "Gödel's Incompleteness Theorems and Artificial Life". Journal of the Society for Philosophy and Technology 2(3-4):142-57.

29. Wheaton, Blair. (2003). "When Methods Make Difference". Current Sociology 51(5):543-571. Sage Publications.

30. Wolfe, Alan (1991), Mind, Self, Society, and Computer: Artificial Intelligence and The Sociology of Mind, dalam American Journal of Sociology, Vol.96, Issue 5, The University of Chicago Press, hal. 1073-1096.


Repository Staff Only: item control page