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by Keyword: Convergent validation


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Verschure, P., (2018). A chronology of Distributed Adaptive Control Living machines: A handbook of research in biomimetics and biohybrid systems (ed. Prescott, T. J., Lepora, Nathan, Verschure, P.), Oxford Scholarship (Oxford, UK) , 346-360

This chapter presents the Distributed Adaptive Control (DAC) theory of the mind and brain of living machines. DAC provides an explanatory framework for biological brains and an integration framework for synthetic ones. DAC builds on several themes presented in the handbook: it integrates different perspectives on mind and brain, exemplifies the synthetic method in understanding living machines, answers well-defined constraints faced by living machines, and provides a route for the convergent validation of anatomy, physiology, and behavior in our explanation of biological living machines. DAC addresses the fundamental question of how a living machine can obtain, retain, and express valid knowledge of its world. We look at the core components of DAC, specific benchmarks derived from the engagement with the physical and the social world (the H4W and the H5W problems) in foraging and human–robot interaction tasks. Lastly we address how DAC targets the UTEM benchmark and the relation with contemporary developments in AI.

Keywords: Distributed Adaptive Control, Problem of priors, Symbol grounding problem, Convergent validation, Foraging, brain, Architecture, system


Verschure, P., Prescott, T. J., (2018). A living machines approach to the sciences of mind and brain Living Machines: A Handbook of Research in Biomimetic and Biohybrid Systems (ed. Prescott, T. J., Lepora, Nathan, Verschure, P.), Oxford Scholarship (Oxford, UK) , 15-25

How do the sciences of mind and brain—neuroscience, psychology, cognitive science, and artificial intelligence (AI)—stand in relation to each other in the 21st century? This chapter proposes that despite our knowledge expanding at ever-accelerating rates, our understanding of the relationship between mind and brain is, in some important sense, becoming less and less. An increasing explanatory gap can only be bridged by a multi-tiered and integrated theoretical framework that recognizes the value of developing explanations at different levels, combining these into cross-level integrated theories, and directly contributing to new technologies that improve the human condition. Development of technologies that instantiate principles gleaned from the study of the mind and brain, or biomimetic technologies, is a key part of the validation process for scientific theories of mind and brain. We call this strategy for the integration of science and engineering a Living Machines approach. Following this path can lead not only to better science, and useful engineering, but also a richer view of human experience and of relationships between science, engineering, and art.

Keywords: Convergent validation, Multi-tiered theories, Paradigms in cognitive science, Philosophy of science, Physical models, Reductionism