Settable systems: An extension of Pearl's Causal model with optimization, equilibrium, and learning

Journal of Machine Learning Research

Volumn 10, Issue , 2009, Pages 1759-1799

  White, Halbert ^a   Chalak, Karim ^b  

^a Department of Economics   (United States)

^b BOSTON COLLEGE   (United States)

Author keywords

Causal models; Game theory; Machine learning; Recursive estimation; Simultaneous equations

Indexed keywords

CAUSAL MODEL; CAUSAL MODELS; CAUSAL RELATIONS; COMMON FEATURES; DUAL ROLE; EXOGENOUS VARIABLES; FIXED POINTS; INTERACTING AGENTS; MACHINE LEARNING; RECURSIVE ESTIMATION; RELATED MACHINES; RESPONSE FUNCTIONS; SIMULTANEOUS EQUATIONS; SOCIAL SYSTEMS; SYSTEM FRAMEWORK; SYSTEMS FRAMEWORK;

ECONOMICS; EDUCATION; GEMS; OPTIMIZATION; PULSE CODE MODULATION; RECURSIVE FUNCTIONS; ROBOT LEARNING;

GAME THEORY;

EID: 70349428511     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article

References (40)

1. D. H. Ackley, G. E. Hinton, and T. J. Sejnowski. A learning algorithm for Boltzmann machines. Cognitive Science, 9:147-169, 1985.
2. C. Berge. Espaces Topologiques. Paris: Dunod (translation by E.M. Patterson, Topological Spaces. Edinburgh: Oliver and Boyd), 1963.
3. K. Chalak and H. White. An extended class of instrumental variables for the estimation of causal effects. Technical report, Department of Economics, University of California, San Diego, 2008a.
4. K. Chalak and H. White. Independence and conditional independence in causal systems. Technical report, Department of Economics, University of California, San Diego, 2008b.
5. X. Chen and H. White. Nonparametric adaptive learning with feedback. Journal of Economic Theory, 82:190-222, 1998.
6. A.P. Dawid. Influence diagrams for causal modeling and inference. International Statistical Review, 70:161-189, 2002.
7. A. Dempster, N. Laird, and D. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B, 39:1-38, 1977.
8. M. Eichler and V. Didelez. Causal reasoning in graphical time-series models. In Proceedings of the 23rd Annual Conference on Uncertainty in Artificial Intelligence, 2007.
9. J. Elman. Finding structure in time. Cognitive Science, 14:179-211, 1990.
10. F. Fisher. A correspondence principle for simultaneous equations. Econometrica, 38:73-92, 1970.
11. J. Friedman. A noncooperative equilibrium for supergames. Review of Economic Studies, 38:1-12, 1971.
12. D. Geiger, T. S. Verma, and J. Pearl. Identifying independence in Bayesian networks. Networks, 20:507-534, 1990.
13. R. Gibbons. Game Theory for Applied Economists. Princeton: Princeton University Press, 1992.
14. J. Halpern. Axiomatizing causal reasoning. Journal of Artificial Intelligence Research, 12:317-337, 2000.
15. D. Heckerman and R. Shachter. Decision-theoretic foundations for causal reasoning. Journal of Artificial Intelligence Research, 3:405-430, 1995.
16. G. E. Hinton and R. R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313:504-507, 2006. (Pubitemid 44148451)
17. G. E. Hinton and T. J. Sejnowski. Learning and relearning in Boltzmann machines. In D. E. Rumelhart, J. L. McClelland, and the PDP Research Group, editors, Parallel Distributed Processing: Explorations in the Microstructure of Cognition, volume 1, pages 282-317. Cambridge: MIT Press, 1986.
18. G. E. Hinton, S. Osindero, and Y. W. Teh. A fast learning algorithm for deep belief nets. Neural Computation, 18:1527-1554, 2006. (Pubitemid 44024729)
19. P. Holland. Statistics and causal inference. Journal of the American Statistical Association, 81: 945-970, 1986.
20. R.A. Howard and J. E. Matheson. Influence diagrams. In R.A. Howard and J.E. Matheson, editors, Readings in the Principles and Applications of Decision Analysis. Menlo Park, CA: Strategic Decisions Group, 1984.
21. M. Jordan. Constrained supervised learning. Journal of Mathematical Psychology, 36:396-425, 1992.
22. R. Kalman. A new approach to linear filtering and prediction problems. Transactions of the ASME, Series D, Journal of Basic Engineering, 82:35-45, 1960.
23. D. Koller and B. Milch. Multi-agent influence diagrams for representing and solving games. Games and Economic Behavior, 45:181-221, 2003.
24. C.-M. Kuan, K. Hornik, and H. White. A convergence result for learning in recurrent neural networks. Neural Networks, 6:420-440, 1994.
25. H. Kushner and D. Clark. Stochastic Approximation Methods for Constrained and Unconstrained Systems. Berlin: Springer-Verlag, 1978.
26. L. Ljung and T. Soderstrom. Theory and Practice of Recursive Identification. Cambridge, MA: MIT Press, 1983.
27. J. Marsden and A. Tromba. Vector Calculus. New York: W.H. Freeman, 5th edition, 2003.
28. J. Nash. Equilibrium points in n-person games. In Proceedings of the National Academy of Sciences, volume 36, pages 48-49, 1950.
29. L.G. Neuberg. Review of Causality: Models, Reasoning, and Inference. Econometric Theory, 19: 675-685, 2003.
30. J. Pearl. Causality. New York: Cambridge University Press, 2000.
31. H. Robbins and S. Monro. A stochastic approximation method. Annals of Mathematical Statistics, 22:400-407, 1951.
32. S. Schennach, H. White, and K. Chalak. Estimating average marginal effects in nonseparable structural systems. Technical report, Department of Economics, University of California, San Diego, 2008.
33. Y. Sergeyev and V. Grishagin. Parallel asynchronous global search and the nested optimization scheme. Journal of Computational Analysis and Applications, 3:123-145, 2001. (Pubitemid 33690385)
34. B. Shipley. Cause and Correlation in Biology: A User's Guide to Path Analysis, Structural Equations and Causal Inference. Cambridge University Press, 2000.
35. R. Strotz and H. Wold. Recursive vs. nonrecursive systems: An attempt at synthesis. Econometrica, 28:417-427, 1960.
36. S. van Huffel and P Lemmerling. Total Least Squares and Errors-In-Variable s Modeling: Analysis, Algorithms and Applications. Berlin: Springer-Verlag, 2002.
37. H. White. Asymptotic Theory for Econometricians. New York: Academic Press, 2001.
38. H. White. Time-series estimation of the effects of natural experiments. Journal of Econometrics, 135:527-566, 2006.
39. H. White and K. Chalak. Identifying effects of endogenous causes in nonseparable systems using covariates. Technical report, Department of Economics, University of California, San Diego, 2007.
40. H. White and P. Kennedy. Retrospective estimation of causal effects through time. In J. Castle and N. Shephard, editors, The Methodology and Practice of Econometrics: A Festschrift in Honour of David Hendry. Oxford: Oxford University Press, 2009.