Cognition as Embodied Morphological Computation

Cognitive science is considered to be the study of mind (consciousness and thought) and intelligence in humans. Under such definition variety of unsolved/unsolvable problems appear. This article argues for a broad understanding of cognition based on empirical results from i.a. natural sciences, self-organization, artificial intelligence and artificial life, network science and neuroscience, that apart from the high level mental activities in humans, includes sub-symbolic and sub-conscious processes, such as emotions, recognizes cognition in other living beings as well as extended and distributed/social cognition. The new idea of cognition as complex multiscale phenomenon evolved in living organisms based on bodily structures that process information, linking cognitivists and EEEE (embodied, embedded, enactive, extended) cognition approaches with the idea of morphological computation (info-computational self-organisation) in cognizing agents, emerging in evolution through interactions of a (living/cognizing) agent with the environment

Mapping Equivalence for Symbolic Sequences: Theory and Applications

Processing of symbolic sequences represented by mapping of symbolic data into numerical signals is commonly used in various applications. It is a particularly popular approach in genomic and proteomic sequence analysis. Numerous mappings of symbolic sequences have been proposed for various applications. It is unclear however whether the processing of symbolic data provides an artifact of the numerical mapping or is an inherent property of the symbolic data. This issue has been long ignored in the engineering and scientific literature. It is possible that many of the results obtained in symbolic signal processing could be a byproduct of the mapping and might not shed any light on the underlying properties embedded in the data. Moreover, in many applications, conflicting conclusions may arise due to the choice of the mapping used for numerical representation of symbolic data. In this paper, we present a novel framework for the analysis of the equivalence of the mappings used for numerical representation of symbolic data. We present strong and weak equivalence properties and rely on signal correlation to characterize equivalent mappings. We derive theoretical results which establish conditions for consistency among numerical mappings of symbolic data. Furthermore, we introduce an abstract mapping model for symbolic sequences and extend the notion of equivalence to an algebraic framework. Finally, we illustrate our theoretical results by application to DNA sequence analysis

Nature as a Network of Morphological Infocomputational Processes for Cognitive Agents

This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological computational models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted

Digital Signal Processing

Contains an introduction and reports on twenty research projects.National Science Foundation (Grant ECS 84-07285)U.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)National Science Foundation FellowshipSanders Associates, Inc.U.S. Air Force - Office of Scientific Research (Contract F19628-85-K-0028)Canada, Bell Northern Research ScholarshipCanada, Fonds pour la Formation de Chercheurs et l'Aide a la Recherche Postgraduate FellowshipCanada, Natural Science and Engineering Research Council Postgraduate FellowshipU.S. Navy - Office of Naval Research (Contract N00014-81-K-0472)Fanny and John Hertz Foundation FellowshipCenter for Advanced Television StudiesAmoco Foundation FellowshipU.S. Air Force - Office of Scientific Research (Contract F19628-85-K-0028

Digital Signal Processing

Contains an introduction and reports on fourteen research projects.National Science Foundation FellowshipNational Science Foundation (Grant ECS84-07285)U.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)Sanders Associates, Inc.U.S. Air Force - Office of Scientific Research (Contract F19628-85-K-0028)Advanced Television Research ProgramAmoco Foundation FellowshipHertz Foundation Fellowshi

Table of Contents

Contains the table of contents

Digital Signal Processing

Contains an introduction and reports on fifteen research projects.National Science Foundation FellowshipU.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)National Science Foundation (Grant ECS 84-07285)Sanders Associates, Inc.U.S. Air Force - Office of Scientific Research (Contract F19628-85-K-0028)AT&T Bell Laboratories Doctoral Support ProgramCanada, Bell Northern Research ScholarshipCanada, Fonds pour la Formation de Chercheurs et /'Aide a la Recherche Postgraduate FellowshipCanada, Natural Science and Engineering Research Council Postgraduate FellowshipAmoco Foundation FellowshipFannie and John Hertz Foundation Fellowshi

Sustainability and Trust for Artificial Intelligence Technologies

Hammer B, van der Aalst W, Bauckhage C, et al. Sustainability and Trust for Artificial Intelligence Technologies.; 2020

Cognition as Morphological/Morphogenetic Embodied Computation In Vivo

Cognition, historically considered uniquely human capacity, has been recently found to be the ability of all living organisms, from single cells and up. This study approaches cognition from an info-computational stance, in which structures in nature are seen as information, and processes (information dynamics) are seen as computation, from the perspective of a cognizing agent. Cognition is understood as a network of concurrent morphological/morphogenetic computations unfolding as a result of self-assembly, self-organization, and autopoiesis of physical, chemical, and biological agents. The present-day human-centric view of cognition still prevailing in major encyclopedias has a variety of open problems. This article considers recent research about morphological computation, morphogenesis, agency, basal cognition, extended evolutionary synthesis, free energy principle, cognition as Bayesian learning, active inference, and related topics, offering new theoretical and practical perspectives on problems inherent to the old computationalist cognitive models which were based on abstract symbol processing, and unaware of actual physical constraints and affordances of the embodiment of cognizing agents. A better understanding of cognition is centrally important for future artificial intelligence, robotics, medicine, and related fields