Deep learning and punctuated equilibrium theory

Cognitive Systems Research

Volumn 45, Issue , 2017, Pages 59-69

  Hegelich, Simon ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Backpropagation; Deep learning; Neural networks; Policy process; Punctuated equilibrium

Indexed keywords

BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; BUDGET CONTROL; DEEP NEURAL NETWORKS; NEURAL NETWORKS;

MODEL COMPLEXES; POLICY PROCESS; POLITICAL SCIENCE; POLITICAL SYSTEMS; PUNCTUATED EQUILIBRIUM; THEORETICAL FOUNDATIONS;

DEEP LEARNING;

ALGORITHM; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACKPROPAGATION ALGORITHM; DATA PROCESSING; DEEP LEARNING; DEEP NEURAL NETWORK; MACHINE LEARNING; MATHEMATICAL COMPUTING; MEASUREMENT ACCURACY; MEASUREMENT NOISE; MODEL; NOISE; POLICY; POLITICS; PREDICTION; PRIORITY JOURNAL; PUNCTUATED EQUILIBRIUM THEORY; RECEIVER OPERATING CHARACTERISTIC; THEORY;

EID: 85019642130     PISSN: None     EISSN: 13890417     Source Type: Journal    
DOI: 10.1016/j.cogsys.2017.02.006     Document Type: Article

References (33)

1. Baumgartner, F. R., & Epp, D. A. (2013). Explaining punctuations. In Annual meeting of the comparative agendas project, Antwerpen.
2. Berk, R.A., An introduction to ensemble methods for data analysis. Sociological Methods & Research 34:3 (2006), 263–295.
3. Box, G.E., Robustness in the strategy of scientific model building. Robustness in Statistics 1 (1979), 201–236.
4. Breunig, C., Jones, B.D., Stochastic process methods with an application to budgetary data. Political Analysis 19:1 (2011), 103–117.
5. Breunig, C., Koski, C., The tortoise or the hare? incrementalism, punctuations, and their consequences. Policy Studies Journal 40:1 (2012), 45–68.
6. Dowding, K., Hindmoor, A., Martin, A., The comparative policy agendas project: Theory, measurement and findings. Journal of Public Policy, 2015, 1–23.
7. Elman, J.L., Learning and development in neural networks. Cognition 48:1 (1993), 71–99.
8. Epp, D.A., Baumgartner, F.R., Complexity, capacity, and budget punctuations. Policy Studies Journal, 2016.
9. Flink, C.M., Rethinking punctuated equilibrium theory: A public administration approach to budgetary changes. Policy Studies Journal, 2015.
10. Friedman, J., Hastie, T., Tibshirani, R., The elements of statistical learning. Springer series in statistics, Vol. 1, 2001, Springer, Berlin.
11. Gers, F.A., Schmidhuber, J., Cummins, F., Learning to forget: Continual prediction with lstm. Neural Computation 12:10 (2000), 2451–2471.
12. Harvey, A.C., Todd, P., Forecasting economic time series with structural and box-jenkins models: A case study. Journal of Business & Economic Statistics 1:4 (1983), 299–307.
13. Hegelich, S., Decision trees and random forests: Machine learning techniques to classify rare events. European Policy Analysis (EPA) 2:1 (2016), 98–120.
14. Hegelich, S., Fraune, C., Knollmann, D., Point predictions and the punctuated equilibrium theory: A data mining approach – Us nuclear policy as proof of concept. Policy Studies Journal 43:2 (2015), 228–256.
15. Howlett, M., Process sequencing policy dynamics: Beyond homeostasis and path dependency. Journal of Public Policy 29:03 (2009), 241–262.
16. James, G., Witten, D., Hastie, T., Tibshirani, R., An introduction to statistical learning, Vol. 112, 2013, Springer.
17. Jensen, J.L., Mortensen, P.B., Serritzlew, S., The dynamic model of choice for public policy reconsidered: A formal analysis with an application to us budget data. Journal of Public Administration Research and Theory, 2015, muv007.
18. John, P., Bevan, S., What are policy punctuations? large changes in the legislative agenda of the uk government, 1911–2008. Policy Studies Journal 40:1 (2012), 89–108.
19. Jones, B.D., Bounded rationality and political science: Lessons from public administration and public policy. Journal of Public Administration Research and Theory 13:4 (2003), 395–412.
20. Jones, B.D., The comparative policy agendas projects as measurement systems: response to dowding, hindmoor and martin. Journal of Public Policy, 2015, 29–44.
21. Jones, B.D., Baumgartner, F.R., The politics of attention: How government prioritizes problems. 2005, University of Chicago Press.
22. Jones, B.D., Baumgartner, F.R., From there to here: Punctuated equilibrium to the general punctuation thesis to a theory of government information processing. Policy Studies Journal 40:1 (2012), 1–20.
23. Jones, B.D., Baumgartner, F.R., Breunig, C., Wlezien, C., Soroka, S., Foucault, M., François, A., Green-Pedersen, C., Koski, C., John, P., et al. A general empirical law of public budgets: A comparative analysis. American Journal of Political Science 53:4 (2009), 855–873.
24. Jones, B.D., Baumgartner, F.R., True, J.L., Policy punctuations: Us budget authority, 1947–1995. The Journal of Politics 60:01 (1998), 1–33.
25. Jones, B.D., Sulkin, T., Larsen, H.A., Policy punctuations in american political institutions. American Political Science Review 97:01 (2003), 151–169.
26. Jones, B.D., Zalányi, L., Érdi, P., An integrated theory of budgetary politics and some empirical tests: The us national budget, 1791–2010. American Journal of Political Science 58:3 (2014), 561–578.
27. Langley, P., Simon, H.A., Applications of machine learning and rule induction. Communications of the ACM 38:11 (1995), 54–64.
28. Lewis, N., Deep learning made easy with R: A gentle introduction for data science. 2016, CreateSpace Independent Publishing Platform.
29. March, J.G., Simon, H.A., Organizations. 1958, Wiley.
30. Simon, H., Public administration in today's world of organizations and markets. PS: Political Science & Politics 33:04 (2000), 749–756.
31. Simon, H.A., A behavioral model of rational choice. The Quarterly Journal of Economics, 1955, 99–118.
32. Thomas III, H. F. (2016). Contagion in policy agendas: Inferences from an agent-based model of issue attention. In MPSA annual conference.
33. Werbos, P.J., The roots of backpropagation: From ordered derivatives to neural networks and political forecasting, Vol. 1, 1994, John Wiley & Sons.