Efficient Cognition The Evolution Of Representational Decision Making
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Efficient Cognition
An argument that representational decision making is more cognitively efficient, allowing an organism to adjust more easily to changes in the environment. Many organisms (including humans) make decisions by relying on mental representations. Not simply a reaction triggered by perception, representational decision making employs high-level, non-perceptual mental states with content to manage interactions with the environment. A person making a decision based on mental representations, for example, takes a step back from her perceptions at the time to assess the nature of the world she lives in. But why would organisms rely on representational decision making, and what evolutionary benefits does this reliance provide to the decision maker? In Efficient Cognition, Armin Schulz argues that representational decision making can be more cognitively efficient than non-representational decision making. Specifically, he shows that a key driver in the evolution of representational decision making is that mental representations can enable an organism to save cognitive resources and adjust more efficiently to changed environments. After laying out the foundations of his argument—clarifying the central questions, the characterization of representational decision making, and the relevance of an evidential form of evolutionary psychology—Schulz presents his account of the evolution of representational decision making and critically considers some of the existing accounts of the subject. He then applies his account to three open questions concerning the nature of representational decision making: the extendedness of decision making, and when we should expect cognition to extend into the environment; the specialization of decision making and the use of simple heuristics; and the psychological sources of altruistic behaviors.
Structure, Evidence, and Heuristic
This book is the first systematic treatment of the philosophy of science underlying evolutionary economics. It does not advocate an evolutionary approach towards economics, but rather assesses the epistemic value of appealing to evolutionary biology in economics more generally. The author divides work in evolutionary economics into three distinct, albeit related, forms: a structural form, an evidential form, and a heuristic form. He then analyzes five examples of work in evolutionary economics falling under these three forms. For the structural form, he examines the parallelism between natural selection and economic decision making, and the parallelism between natural selection and market competition. For the evidential form, he looks at the relationship between animal and human economic decision making, and the evolutionary explanation of diversity in human economic decision making. Finally, for the heuristic form, he focuses on the plausibility of equilibrium modeling in evolutionary ecology and economics. In this way, he shows that linking evolutionary biology and economics can make for a powerful methodological tool that can enable progress in our understanding of various economics questions. Structure, Evidence, and Heuristic will be of interest to scholars and advanced students working in philosophy of science, philosophy of social science, evolutionary biology, and economics.
Explorations in Archaeology and Philosophy
This volume explores various themes at the intersection of archaeology and philosophy: inference and theory; interdisciplinary connections; cognition, language and normativity; and ethical issues. Showcasing this heterogeneity, its scope ranges from the method of analogical inference to the evolution of the human mind; from conceptual issues in assessing the health of past populations to the ethics of cultural heritage tourism. It probes the archaeological record for evidence of numeracy, curiosity and creativity, and social complexity. Its contributors comprise an interdisciplinary cluster of philosophers, archaeologists, anthropologists, and psychologists, from a variety of career stages, of whom many are leading experts in their fields. Chapter 3 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.