To function in an unpredictable environment using unreliable components, a system must be robust. Robustness is critical to biological systems and is an objective in the design of engineered systems. For example, temperature-dependent chemical reactions that produce circadian rhythms must occur in a precise manner despite great variation in ambient temperature, and airplane engines must produce adequate thrust across a range of altitudes. The human cognitive system, like biological and engineered systems, exists within a variable environment. This raises the question, how does the cognitive system achieve similarly high degrees of robustness?
This question has inspired two parallel lines of research. The first involves developing a quantitative method to supplant current qualitative definitions of robustness in cognitive science. The second involves identifying mechanisms that enhance robustness.
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Walsh, M. M., Einstein, E. H., & Gluck, K. A. (2013). A quantification of robustness. Journal of Applied Research in Memory and Cognition, 2, 137-148.
Walsh, M. M., & Gluck, K. A. (in press). Mechanisms for robust cognition. Cognitive Science.
Gluck, K. A., McNamara, J. M., Brighton, H., Dayan, P., Kareev, Y., Krause, J., Kurzban, R., Selten, R., Stevens, J. R., Voelkl, B., & Wimsatt, W. C. (2012). Robustness in a variable environment. In Stevens, J. R. & P. Hammerstein (Eds.) Evolution and the mechanisms of decision making. Strüngmann Forum Report, vol. 11, J. Lupp, series ed. Cambridge, MA: MIT Press.
Matthew Walsh 