4,637 research outputs found

    The challenge of complexity for cognitive systems

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    Complex cognition addresses research on (a) high-level cognitive processes – mainly problem solving, reasoning, and decision making – and their interaction with more basic processes such as perception, learning, motivation and emotion and (b) cognitive processes which take place in a complex, typically dynamic, environment. Our focus is on AI systems and cognitive models dealing with complexity and on psychological findings which can inspire or challenge cognitive systems research. In this overview we first motivate why we have to go beyond models for rather simple cognitive processes and reductionist experiments. Afterwards, we give a characterization of complexity from our perspective. We introduce the triad of cognitive science methods – analytical, empirical, and engineering methods – which in our opinion have all to be utilized to tackle complex cognition. Afterwards we highlight three aspects of complex cognition – complex problem solving, dynamic decision making, and learning of concepts, skills and strategies. We conclude with some reflections about and challenges for future research

    Stigmergic epistemology, stigmergic cognition

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    To know is to cognize, to cognize is to be a culturally bounded, rationality-bounded and environmentally located agent. Knowledge and cognition are thus dual aspects of human sociality. If social epistemology has the formation, acquisition, mediation, transmission and dissemination of knowledge in complex communities of knowers as its subject matter, then its third party character is essentially stigmergic. In its most generic formulation, stigmergy is the phenomenon of indirect communication mediated by modifications of the environment. Extending this notion one might conceive of social stigmergy as the extra-cranial analog of an artificial neural network providing epistemic structure. This paper recommends a stigmergic framework for social epistemology to account for the supposed tension between individual action, wants and beliefs and the social corpora. We also propose that the so-called "extended mind" thesis offers the requisite stigmergic cognitive analog to stigmergic knowledge. Stigmergy as a theory of interaction within complex systems theory is illustrated through an example that runs on a particle swarm optimization algorithm

    Review Essay: Andy Clark, Natural-Born Cyborgs: Minds, Technologies, and the Future of Human Intelligence.

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    Review Essay: Andy Clark, Natural-Born Cyborgs: Minds, Technologies, and the Future of Human Intelligence

    Sharedness and privateness in human early social life

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    This research is concerned with the innate predispositions underlying human intentional communication. Human communication is currently defined as a circular and overt attempt to modify a partner's mental states. This requires each party involved to posse ss the ability to represent and understand the other's mental states, a capability which is commonly referred to as mindreading, or theory of mind (ToM). The relevant experimental literature agrees that no such capability is to be found in the human speci es at least during the first year of life, and possibly later. This paper aims at advancing a solution to this theoretical problem. We propose to consider sharedness as the basis for intentional communication in the infant and to view it as a primitive, i nnate component of her cognitive architecture. Communication can then build upon the mental grounds that the infant takes as shared with her caregivers. We view this capability as a theory of mind in a weak sense.

    A Non Monotonic Reasoning framework for Goal-Oriented Knowledge Adaptation

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    In this paper we present a framework for the dynamic and automatic generation of novel knowledge obtained through a process of commonsense reasoning based on typicality-based concept combination. We exploit a recently introduced extension of a Description Logic of typicality able to combine prototypical descriptions of concepts in order to generate new prototypical concepts and deal with problem like the PET FISH (Osherson and Smith, 1981; Lieto & Pozzato, 2019). Intuitively, in the context of our application of this logic, the overall pipeline of our system works as follows: given a goal expressed as a set of properties, if the knowledge base does not contain a concept able to fulfill all these properties, then our system looks for two concepts to recombine in order to extend the original knowledge based satisfy the goal

    Review for Cognitive Systems Research of the book The Brain and AI, by authors Karl Schlagenhauf and Fanji Gu

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    The human brain is often considered the most complex system known. It has a fantastic capacity to learn and remember, to recognize patterns in space and time, solve problems of all kinds, innovate tools and machines, create beautiful art and science. Is it reasonable to believe that we, in a foreseeable future, will be able to understand all the wonders of our own brain, enough to be able to mimic it and build artificial brains and minds that correspond to or even surpass the capacity of the human origin? Can we seriously believe that we (soon, or ever) will be able to build robots that know of and can reflect upon their own existence?This review of the book, The Brain and AI, deals with such issues, but in a very special way. It is written as a fascinating dialogue between the two authors, Chinese scientist Fanji Gu and German engineer Karl Schlagenhauf, where they discuss the development of neuroscience and artificial intelligence (AI) with a critical examination of given "truths" in these fields. The Brain and AI is indeed worth reading for many reasons, regardless if you are a student or researcher in any of the many fields of science discussed here (e.g. physics, computer science, neuroscience, cognitive science psychology, social science), or if you are just interested in the current and future development of brain research and artificial intelligence. The book is both educating and entertaining and can be strongly recommended. (C) 2020 The Author. Published by Elsevier B.V

    Stigmergic epistemology, stigmergic cognition

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    To know is to cognize, to cognize is to be a culturally bounded, rationality-bounded and environmentally located agent. Knowledge and cognition are thus dual aspects of human sociality. If social epistemology has the formation, acquisition, mediation, transmission and dissemination of knowledge in complex communities of knowers as its subject matter, then its third party character is essentially stigmergic. In its most generic formulation, stigmergy is the phenomenon of indirect communication mediated by modifications of the environment. Extending this notion one might conceive of social stigmergy as the extra-cranial analog of an artificial neural network providing epistemic structure. This paper recommends a stigmergic framework for social epistemology to account for the supposed tension between individual action, wants and beliefs and the social corpora. We also propose that the so-called ‘‘extended mind’’ thesis offers the requisite stigmergic cognitive analog to stigmergic knowledge. Stigmergy as a theory of interaction within complex systems theory is illustrated through an example that runs on a particle swarm optimization algorithm.Social epistemology; Extended mind; Social cognition; Particle swarm optimization
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