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dr. H.J. (Henry) Brighton

Assistant Professor 

Tilburg School of Humanities and Digital Sciences
Department Cognitive Science and Artificial Intelligence


How do humans and other animals function so effectively in such an uncertain world, and can an understanding of this ability guide the development of computational intelligence? I study these issues by examining how environmental uncertainty regulates decision making, learning, evolutionary and adaptive systems, and cultural processes.

My research typically involves computational modelling, but also experiments with human subjects. I have made key contributions to the computational modelling of the evolution of language, bounded and ecological rationality, and instance-based learning. My book Introducing Artificial Intelligence is an illustrated guide to the big ideas in artificial intelligence.

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Principal publications

  • Moussaïd, M., Brighton, H., & Gaissmaier, W. (2015). The amplification of risk in experimental diffusion chains. Proceedings of the National Academy of Sciences of the USA, 112, 5631-5636. doi:10.1073/pnas.1421883112
  • Brighton, H. & Gigerenzer, G. (2015). The bias bias. Journal of Business Research, 68, 1772-1784. doi:10.1016/j.jbusres.2015.01.061
  • Gigerenzer, G. & Brighton, H. (2009). Homo heuristicus: Why biased minds make better inferences. Topics in Cognitive Science, 1, 107-143. doi:10.1111/j.1756-8765.2008.01006.x
  • Brighton, H. Kirby, S. & Smith, K. (2005). Language as an evolutionary system. Physics of Life Reviews, 2, 177-226. doi:10.1016/j.plrev.2005.06.001
  • Brighton, H. & Mellish, C. S. (2002). Advances in instance selection for instance-based learning algorithms. Data Mining and Knowledge Discovery, 6, 153-172. doi:10.1023/A:1014043630878
Last amended: 20 February 2018