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  1. Theoretical neuroscience: computational and mathematical modeling of neural systems.Peter Dayan & L. Abbott - 2001 - Philosophical Psychology 15 (4):563-577.
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  • Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.Judea Pearl - 1988 - Morgan Kaufmann.
    The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
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  • (3 other versions)Causal learning: psychology, philosophy, and computation.Alison Gopnik & Laura Schulz (eds.) - 2007 - New York: Oxford University Press.
    Understanding causal structure is a central task of human cognition. Causal learning underpins the development of our concepts and categories, our intuitive theories, and our capacities for planning, imagination and inference. During the last few years, there has been an interdisciplinary revolution in our understanding of learning and reasoning: Researchers in philosophy, psychology, and computation have discovered new mechanisms for learning the causal structure of the world. This new work provides a rigorous, formal basis for theory theories of concepts and (...)
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  • Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment.Amos Tversky & Daniel Kahneman - 1983 - Psychological Review 90 (4):293-315.
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  • (1 other version)Bayesian theories of conditioning in a changing world.Aaron C. Courville, Nathaniel D. Daw & David S. Touretzky - 2006 - Trends in Cognitive Sciences 10 (7):294-300.
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