COMPUTATION, INFORMATION, COGNITION - Gordana Dodig Crnkovic and Susan Stuart (original) (raw)
Related papers
Discussion on the Relationship between Computation, Information, Cognition, and Their Embodiment
Entropy, 2023
Three special issues of Entropy journal have been dedicated to the topics of “Information-Processing and Embodied, Embedded, Enactive Cognition”. They addressed morphological computing, cognitive agency, and the evolution of cognition. The contributions show the diversity of views present in the research community on the topic of computation and its relation to cognition. This paper is an attempt to elucidate current debates on computation that are central to cognitive science. It is written in the form of a dialog between two authors representing two opposed positions regarding the issue of what computation is and could be, and how it can be related to cognition. Given the different backgrounds of the two researchers, which span physics, philosophy of computing and information, cognitive science, and philosophy, we found the discussions in the form of Socratic dialogue appropriate for this multidisciplinary/cross-disciplinary conceptual analysis. We proceed as follows. First, the proponent (GDC) introduces the info-computational framework as a naturalistic model of embodied, embedded, and enacted cognition. Next, objections are raised by the critic (MM) from the point of view of the new mechanistic approach to explanation. Subsequently, the proponent and the critic provide their replies. The conclusion is that there is a fundamental role for computation, understood as information processing, in the understanding of embodied cognition.
Computation and cognition: Issues in the foundations of cognitive science
Behavioral and Brain Sciences, 1980
Abstract: The computational view of mind rests on certain intuitions regarding the fundamental similarity between computation and cognition. We examine some of these intuitions and suggest that they derive from the fact that computers and human organisms ...
INFORMATION AND COMPUTATION - Gordana Dodig Crnkovic and Mark Burgin
Information And Computation: Essays On Scientific And Philosophical Understanding Of Foundations Of Information And Computation, 2011
Information is a basic structure of the world, while computation is a process of the dynamic change of information. This book provides a cutting-edge view of world's leading authorities in fields where information and computation play a central role. It sketches the contours of the future landscape for the development of our understanding of information and computation, their mutual relationship and the role in cognition, informatics, biology, artificial intelligence, and information technology. This book is an utterly enjoyable and engaging read which gives readers an opportunity to understand and relate phenomena seemingly unrelated in a completely new light - especially the connections between information, computation, cognition and life. GOOGLE BOOK https://www.amazon.ca/Information-Computation-Philosophical-Understanding-Foundations/dp/B00ITY9GTU/ref=sr\_1\_1?keywords=INFORMATION+AND+COMPUTATION+-+Gordana+Dodig+Crnkovic+and+Mark+Burgin&qid=1578174785&s=books&sr=1-1
Computation and Cognition: Four distinctions and their implications
In this paper I discuss four computational distinctions at the heart of natural computation, and thus relevant to the central and most interesting question of cognitive science: "how the brain computes the mind". I assume that we can think of cognition as a form of computation, implemented by the tissues of the nervous system, and that the unification of high-level computational theories of cognitive function with detailed, local-level understanding of synapses and neurons is the core goal of cognitive (neuro)science. Thus I am concerned here with how the brain computes the mind, following Alan Turing's seminal gambit , and much of subsequent cognitive science, in thinking that intelligence is a kind of computation performed by the brain. By thus asserting that the brain is a kind of computer, I must immediately clarify that the natural computations performed by the brain differ dramatically from those implemented by modern digital computers . Computation (the acquisition, processing and transformation of information) is a more general process than the serial, binary computation performed by common digital computers. From this viewpoint, the assertion that the brain is a kind of computer is a mild one. It amounts to nothing but the everyday assumption that the brain is an organ responsible for acquiring, remembering, processing and evaluating sensory stimuli, and using the knowledge thus acquired to plan and generate appropriate action.
2000
Information, Computation, and the Nature of Cognition: A Critique of Computational Approaches to Understanding and Creating Minds Cognitive scientists generally subscribe to an information-processing model of mind and implement this model through computational methods. Information processing is understood to be generation and composition of informational primitives into more complex pieces of information in response to signals extracted from the environment. Computationalism offers a powerful methodology for carrying out information processing, with abstract tokens standing in for pieces of information, and new information structures being created through application of rules. This purely syntactic model of cognition is unable, however, to explain the nature of semantic information. Modifications of Shannon information theory and applications of principles of natural selection fail to provide a non-syntactic account of the nature and origin of semantic information. Purely syntactic explanations of semantic information fail to capture the representational capabilities of true cognitive agents. Relying on computational explanations of cognitive behavior leads not only to an explanatory gap, but also to practical failings. These failings constitute the specific and general frame problems. To avoid these problems, a model of cognition that focuses on the adaptive capabilities of its realizing hardware must be adopted. Evolutionary and ecological models only provide pieces of a final theory. A high-level model for cognition can be found in the field of complex and self-organizing systems, a branch of viii dynamic systems theory. One possible characterization of the lower-level mechanisms responsible for the high-level behavior is given by Edelman's Theory of Neuronal Group Selection. What emerges is a theory with strong similarities to behaviorism and teleological functionalism, although without the deficiencies of either theory. This theory offers the foundation for a new understanding of the nature of representation and information.
Philosophy of Information, a New Renaissance and the Discreet Charm of the Computational Paradigm
Computing and Philosophy Conference, E-CAP …, 2004
The ontology of each theory is always embedded in natural language with all of its ambiguity. Attempts to automate the communication between different ontologies face the problem of compatibility of concepts with different semantic origins. Coming from different Universes, terms with the same spelling may have a continuum of meanings. The formalization problem met in the semantic web or ontology engineering is thus closely related to the natural language semantic continuum. The emergence of a common context necessary to assure the minimum "common language" is a natural consequence of this process of intense communication that develops in parallel with computationalization of almost every conceivable field of human activity. The necessity of conceptualization of this new global space calls for understanding across the borders of previously relatively independent, locally defined Universes. In that way a need and potential for a new Renaissance, in which sciences and humanities, arts and engineering can reach a new synthesis, has emerged.
The Mindlessness of Computationalism: The Neglected Aspects of Cognition
The emergence of cognitive science as a multi-disciplinary investigation into the nature of mind has historically revolved around the core assumption that the central ‘cognitive’ aspects of mind are computational in character. Although there is some disagreement and philosophical speculation concerning the precise formulation of this ‘core assumption’ it is generally agreed that computationalism in some form lies at the heart of cognitive science as it is currently conceived. Von Eckardt’s recent work on this topic is useful in enabling us to get a sense of the scope of the computational assumption. She makes clear that there are two rather different ways in which we could understand cognitive science’s commitment to computationalism and hence two ways to understand the claim that the ‘mind is a computer’, by appeal to either (1) A mathematical theory of computability or (2) A theory of data-processing or information-processing. Importantly, she also argues that although there are many aspects of claim that the ‘mind is a computer’ that can be nicely captured by Boyd’s account of the way scientific metaphors are employed, not to direct attention to the hitherto unnoticed, but to encourage investigation of the unknown. Nonetheless, cognitive scientists are not making the claim that the ‘mind is a computer’ in a metaphorical sense. If Von Eckhardt is correct, when cognitive scientists assume the ‘mind is a computer’ and give a sense to the notion of the computer in the sense of (2) above, they are making a literal claim about the nature of mind (Von Eckardt, 1993, p. 116). And as she points out that if one reads (2) in a theoretically committed way then there is no a priori reason to exclude the organic brain from the list of entities that might fall under the description of being a ‘computer’. Important, we can truly describe it as a data-processing (or information-processing) device. What is useful about Von Eckardt’s general analysis of computationalism’s core assumption is that it provides a clear angle from which to view the flaws of computationalism. This paper defends the claim that if there is an account of information adequate to capture those aspects of mind that we regard as essential to mentality it is one that requires us to surrender the idea that the mind is a computer.
Artificial Intelligence: Cognition as Computation
1982
: The ability and compulsion to know are as characteristic of our human nature as are our physical posture and our languages. Knowledge and intelligence, as scientific concepts, are used to describe how an organism's experience appears to mediate its behavior. This report discusses the relation between artificial intelligence (AI) research in computer science and the approaches of other disciplines that study the nature of intelligence, cognition, and mind. The state of AI after 25 years of work in the field is reviewed, as are the views of its practitioners about its relation to cognate disciplines. The report concludes with a discussion of some possible effects on our scientific work of emerging commercial applications of AI technology, that is, machines that can know and can take part in human cognitive activities.
Our minds are not computers, or why computers know nothing
2023
This paper briefly introduces some of the central concepts of digital computing in order to aid those without computer science background in thinking accurately about the ontology of computers, including ontological status of data structures, computer 'decision-making', 'artificial intelligence', basic computer architecture and semantics of human-computer interaction.
Cognitive Science and Information
2010
Since the beginning of empirical cognitive science around 1950, cognition is seen as information processing. We present and compare the two central paradigms, symbolism and connectionism, of this branch of cognitive science. The second part of this paper will discuss those functional approaches in terms of their ability to describe mind and consciousness. Therefore we will use a concept of information and show the borderline between syntax and semantics. The outcome of this are requirements for information processing systems that have to be fulfilled to achieve "intelligence" 1 .