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''' Kognitive Modellierung'''
''' Kognitive Modellierung'''
* Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. Current Directions in Psychological Science, 20(3), 160–166.
* Bundesen, C., & Habekost, T. (2007). Models of attention.
* Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. Trends in Cognitive Sciences, 9(9), 424–430.
* Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., … DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science, 310(5750), 987–991.
* Heathcote, A., & Brown, S. (2015). An Introduction to Good Practices in Cognitive An Introduction to Good Practices in Cognitive Modeling. Springer.
* Honing, H. (2006). The role of surprise in theory testing: Some preliminary observations. In Proceedings of the international conference on music perception and cognition (pp. 38–42).
* Izhikevich, E. M. (2007). Solving the distal reward problem through linkage of STDP and dopamine signaling. Cerebral Cortex, 17(10), 2443–2452.
* Kelso, J. A. S. (1997). Dynamic Patterns: The Self-Organization of Behavior.
* Lins, J., & Schöner, G. (2014). A Neural Approach to Cognition Based on Dynamic Field Theory. Neural Fields, 319–339.
* Macho, S. (2002). Cognitive modeling with spreadsheets. Behavior Research Methods, Instruments, and Computers, 34(1), 19–36.
* Mcclelland, J. L. (2009). The Place of Modeling in Cognitive Science. Topics in Cognitive Science, 1(1), 11–38.
* Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion Decision Model: Current Issues and History. Trends in Cognitive Sciences, 20(4), 260–281.
* Rey, G. D., & Wender, K. F. (2008). Neuronale Netze: eine Einführung in die Grundlagen, Anwendungen und Datenauswertung.
* Sandamirskaya, Y., Zibner, S. K. U., Schneegans, S., & Schöner, G. (2013). Using Dynamic Field Theory to extend the embodiment stance toward higher cognition. New Ideas in Psychology, 31(3), 322–339.
* Schoner, G., & Kelso, J. A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), 1513–1520.
* Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).
* Tuller, B., Case, P., Ding, M., & Kelso, J. A. S. (1994). The nonlinear dynamics of speech categorization. Journal of Experimental Psychology: Human Perception and Performance, 20(1), 3–16.
* Wilensky, U., & Resnick, M. (1999). Springer Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World. Source: Journal of Science Education and Technology Journal of Science Education and Technology, 8(1), 3–19.

Version vom 28. August 2018, 15:44 Uhr

Einführung in die Methoden & Versuchsplanung

  • Bortz, J., Döring, N. (2006) Forschungsmethoden und Evaluation. Berlin: Springer
  • Goodwin, C. J. (2009) Research in Psychology. Hoboken NJ: Wiley
  • Hecht, H., Desnizza, W. (2012) Psychologie als empirische Wissenschaft. Berlin: Springer
  • Herzog, W. (2012) Wissenschafts-theoretische Grundlagen der Psychologie. Berlin: Springer
  • Hussy, W., & Jain, A. (2002). Experimentelle Hypothesenprüfung in der Psychologie. Göttingen: Hogrefe
  • Hussy, W., Schreier, M., Echterhoff, G. (2010) Forschungsmethoden in Psychologie und Sozialwissenschaften für Bachelor. Berlin: Springer
  • Kukla, A., & Walmsley, J. (2006). Mind: A Historical and Philosophical Introduction to the Major Theories. Indianapolis: Hackett Publishing
  • Sarris, V. (1992) Methodologische Grundlagen der Experimentalpsychologie, Bd.2, Versuchsplanung und Stadien des psychologischen Experiments. München: UTB
  • Schnell, R., Hill, P.B., Esser, E. (2011) Methoden der empirischen Sozialforschung. München: Oldenbourg
  • Whitley, B.E., Kite, M.E. (2013) Principles of Research in Behavioral Science. New York: Routledge
  • Walach, H. (2013) Psychologie: Wissenschaftstheorie, philosophische Grundlagen und Geschichte. Stuttgart: Kohlhammer


Kognitive Modellierung

  • Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. Current Directions in Psychological Science, 20(3), 160–166.
  • Bundesen, C., & Habekost, T. (2007). Models of attention.
  • Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. Trends in Cognitive Sciences, 9(9), 424–430.
  • Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., … DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science, 310(5750), 987–991.
  • Heathcote, A., & Brown, S. (2015). An Introduction to Good Practices in Cognitive An Introduction to Good Practices in Cognitive Modeling. Springer.
  • Honing, H. (2006). The role of surprise in theory testing: Some preliminary observations. In Proceedings of the international conference on music perception and cognition (pp. 38–42).
  • Izhikevich, E. M. (2007). Solving the distal reward problem through linkage of STDP and dopamine signaling. Cerebral Cortex, 17(10), 2443–2452.
  • Kelso, J. A. S. (1997). Dynamic Patterns: The Self-Organization of Behavior.
  • Lins, J., & Schöner, G. (2014). A Neural Approach to Cognition Based on Dynamic Field Theory. Neural Fields, 319–339.
  • Macho, S. (2002). Cognitive modeling with spreadsheets. Behavior Research Methods, Instruments, and Computers, 34(1), 19–36.
  • Mcclelland, J. L. (2009). The Place of Modeling in Cognitive Science. Topics in Cognitive Science, 1(1), 11–38.
  • Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion Decision Model: Current Issues and History. Trends in Cognitive Sciences, 20(4), 260–281.
  • Rey, G. D., & Wender, K. F. (2008). Neuronale Netze: eine Einführung in die Grundlagen, Anwendungen und Datenauswertung.
  • Sandamirskaya, Y., Zibner, S. K. U., Schneegans, S., & Schöner, G. (2013). Using Dynamic Field Theory to extend the embodiment stance toward higher cognition. New Ideas in Psychology, 31(3), 322–339.
  • Schoner, G., & Kelso, J. A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), 1513–1520.
  • Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).
  • Tuller, B., Case, P., Ding, M., & Kelso, J. A. S. (1994). The nonlinear dynamics of speech categorization. Journal of Experimental Psychology: Human Perception and Performance, 20(1), 3–16.
  • Wilensky, U., & Resnick, M. (1999). Springer Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World. Source: Journal of Science Education and Technology Journal of Science Education and Technology, 8(1), 3–19.