Here are some references for Parameterized Complexity and Cognitive Science
1) The Parameterized Complexity of Approximate Inference in Bayesian Networks. Johan Kwisthout (2016) In A. Antonucci, G. Corani, and C.P. de Campos (Eds.): Proceedings of the Eighth International Conference on Probabilistic Graphical Models (PGM'16), September 5-9, Lugano, Switzerland. Proceedings of Machine Learning Research, 52, pp. 264-274. An invited journal version is under review at the International Journal of Approximate Reasoning.
2) A Computational-level Explanation of the Speed of Goal Inference. Mark Blokpoel, Johan Kwisthout, Theo P. van der Weide, Todd Wareham, and Iris van Rooij (2013) Journal of Mathematical Psychology, 57(3-4), 117 - 133.
3) Bridging the Gap between Theory and Practice of Approximate Bayesian Inference. Johan Kwisthout and Iris van Rooij (2012) In N. Rußwinkel, U. Drewitz, and H. van Rijn (Eds.): Proceedings of the 11th International Conference on Cognitive Modeling, April 16-19, 2012, Berlin, pp. 199-204. A journal version is in press at the Cognitive Systems Research journal.
4) A change for the better? Assessing the computational cost of re-representation. Wareham, T., Robere, R., & van Rooij, I. (2012) In N. Rußwinkel, U. Drewitz, and H. van Rijn (Eds.): Proceedings of the 11th International Conference on Cognitive Modeling, April 16-19, 2012, Berlin, pp. 111-116.
5) What does (and doesn't) make analogical problem solving easy? Wareham, H.T., Evans, P. & van Rooij, I. (2011) Journal of Problem Solving, 3(2), 30-71.
6) On the computational challenges of analogy-based generalization. Wareham, H.T. & van Rooij, I. (2011) Cognitive Systems Research, 12(3-4), 266-280.
7) Communicating Intentions: Computationally Easy or Difficult? Iris van Rooij, Johan Kwisthout, Mark Blokpoel, Jakub Szymanik, Todd Wareham, and Ivan Toni (2011) Frontiers in Human Neuroscience, 5 (52), 1 - 18.
8) The computational costs of recipient design and intention recognition in communication. Mark Blokpoel, Johan Kwisthout, Todd Wareham, Pim Haselager, Ivan Toni, and Iris van Rooij (2011). In L. Carlson, C. Hoelscher, and T.F. Shipley (Eds.): Proceedings of the 33rd Annual Meeting of the Cognitive Science Society, July 20-23, Boston, Massachusetts, pp. 465 - 470.
9) How Action Understanding can be Rational, Bayesian and Tractable. Mark Blokpoel, Johan Kwisthout, Theo van der Weide and Iris van Rooij (2010) In S. Ohlsson and R. Catrambone (Eds.): Proceedings of the 32th Annual Meeting of the Cognitive Science Society, August 11-14, Portland, Oregon, pp. 1643-1648.
10) Similarity as tractable transformation. Müller, M., van Rooij, I., & Wareham, T. (2009) In N. A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 50-55). Austin, TX: Cognitive Science Society.
11) Parameterized Complexity in Cognitive Modeling: Foundations, Applications, and Opportunities. van Rooij, Iris and Wareham, Todd (2008) The Computer Journal, 51(3), 385-404.
12) Commentary: Computational complexity analysis can help, but first we need a theory. Wareham, T., van Rooij, I., and Muller, M. (2008) Behavioral & Brain Sciences, 31(4), 399-400.
13) On the Computational Complexity of Analogy Derivation in the Structure-Mapping Framework. Evans, P., Gedge, J., Muller, M., van Rooij, I., and Wareham, T. (2008) Technical Report 2008-03, Department of Computer Science, Memorial University of Newfoundland.
14) Identifying Sources of Intractability in Cognitive Models: An Illustration using Analogical Structure Mapping. van Rooij, I., Evans, P., Muller, M., Gedge, J., and Wareham, T. (2008) In B.C. Love, K. McRae, and V.M. Sloutsky (eds.) Proceedings of the 30th Annual Meeting of the Cognitive Science Society. Cognitive Science Society; Austin, TX. 915-920.
15) Tractable cognition: Complexity theory in cognitive psychology. van Rooij, I. (2003) PhD thesis, University of Victoria, Canada.
16) The Role of Parameterized Computational Complexity Theory in Cognitive Modeling. Wareham, H.T. (1996) AAAI-96 Workshop Working Notes: Computational Cognitive Modeling: Source of the Power.