In the open system of living cells an info-computational process takes place using DNA, exchanging information, matter, and energy with the environment. All cognizing beings are in constant interaction with their environment.
As a consequence of evolution, increasingly complex living organisms arise. They are able to register inputs data from the environment, to structure those into information and, in more developed organisms, into knowledge. The evolutionary advantage of using structured, component-based approaches data — information — knowledge is improving response time and the computational efficiency of cognitive processes. It also provides the natural solution to the old problem of the role of representation in explaining and producing information, a discussion about two seemingly incompatible views: a symbolic, explicit, and static notion of representation versus an implicit and dynamic interactive one.
Within the info-computational framework, those classical Turing-machine type and connectionist views are reconciled and used to describe different aspects of cognition. The info-computationalist project of naturalizing epistemology by defining cognition as an information-processing phenomenon is based on the development of multilevel dynamical computational models and simulations of intelligent systems and has important consequences for the development of artificial intelligence and artificial life, the subject of the next chapter.
Intelligence, Chess, Computing and AI from Deep Blue to Blue Brain Chess Relevance for AI and Deep Blue Many people would even today agree with the following claim made in If one could devise a successful chess machine, one would seem to have penetrated to the core of human intellectual endeavor. The computer was programmed by a computer scientists assisted by a chess grandmaster. They developed the evaluation function to assess every given position.
This was the beginning of a development of machines dedicated to mimic what would be considered to be intelligent behaviour. Descendant of Deep Blue, Blue Gene an Engine of Scientific Discovery The methods devised in Deep Blue project were employed as a foundation of Blue Gene supercomputer and used among others for protein folding, genetic and brain research. The 7 project was exceptionally fruitful.
Searching for the optimum configurations of systems consisting of simple elements is typical of not only chess play but also of a range of other scientific problems. Solving this category of problems brings us closer to constructing intelligent computers and facilitates scientific progress in general. Blue Brain Project In EPFL and IBM initiated a research project analogous in scope to the Genome Project, with the aim to create a biologically accurate model of the brain using Blue Gene 7 For comparison, Deep Blue had 32 processors and could process about million chess moves per second in its match against Kasparov.
Today Blue Gene uses processors to perform trillion operations per second. This project has already delivered important results with biologically accurate computational neurons made on the basis of experimental data. These neurons are automatically connected in a network by positioning around 30 million synapses in exact 3D locations.
This development from Deep Blue via Deep Gene to the Blue Brain demonstrates how scientific progress can be made through learning by construction. There is a clear paradigm shift in computing as a scientific discipline with respect to classical scientific fields, Dodig Crnkovic Understanding neocortical information processing by reverse-engineering the mammalian brain makes foundation for simulation of the whole brain and is an essential step in our understanding of brain functions including intelligence in info-computational terms, Dodig Crnkovic Promises of the Info-Computational Naturalist Research Programme The central question is how epistemologically productive this paradigm is, as info- computational naturalism really is a research programme whose role is to mobilize researchers to work in the same direction, within the same global framework.
The majority of natural sciences, formal sciences, technical sciences and engineering are already based on computational thinking, computational tools and computational modelling, Wing So the time has come for paradigm change in computing. Present day narrow specialization into different isolated research fields has gradually led into impoverishment of the common world view. In this case, mathematical effectiveness will be replaced by computational effectiveness.
Understanding of the semantics of information as a part of data-information-knowledge- wisdom sequence, in which more and more complex relational structures are created by computational processing of information. An evolutionary naturalist view of semantics of information in living organisms is given based on interaction information exchange of an organism with its environment.
Of special interest are open systems in communication with the environment and related logical pluralism including paraconsistent logic.
Japaridze Advancement of our computing methods beyond the Turing-Church paradigm, computation in the next step of development becoming able to handle complex phenomena such as living organisms and processes of life, knowledge, social dynamics, communication and control of large interacting networks as addressed in organic computing and other kinds of unconventional computing , etc. Of all manifestations of life, mind seems to be information-theoretically and philosophically the most interesting one. On the practical side, understanding and learning to simulate and control functions and structures of living organisms will bring completely new medical treatments for all sorts of diseases including mental ones which to this day are poorly understood.
Understanding of our information-processing features of human brain will bring new insights into such fields as education, media, entertainment, cognition etc. The common for these modern computing systems is that they are ensemble-like as they form one whole in which the parts act in concert to achieve a common goal like an organism that is an ensemble of its cells and physical as ensembles act in the physical world and interact with their environment through sensors and actuators.
Info-computationalism will help us answering the focal research questions and understanding the potential and the limits of the emerging computational paradigm which will have significant impact on the research in both computing and sciences.
It has high relevance for the development of future computing theories and technologies as well as for the improvement of computational models of natural and phenomena. References Ashby , W An introduction to Cybernetics. London: Methuen. Burgin, M. Super-recursive Algorithms. Berlin: Springer Monographs in Computer Science. Chaisson, E. Cosmic Evolution. Chaitin, G.
In Dodig Crnkovic and Stuart Ed. Newcastle : Cambridge Scholars Publishing. World Scientific : World Scientific.
Charness, N. Psychological Research, 54, 4 - 9. Copeland, J. Minds and Machines, 12 , Dodig Crnkovic, G. Investigations into information semantics and ethics of computing.
Epistemology Naturalized: the Info-Computationalist Approach. Semantics of Information as Interactive Computation. Information and Computation. Singapore: World Scientific. Floridi, L. Defence of Informational Structural Realism. Synthese, 2 , Against Digital Ontology. Synthese, 1 , Fredkin, E.
Digital Philosophy. New York: Freeman. Goldin , D. Interactive Computation: the New Paradigm. Goldin, D.
The classical of eight issues on Venice offers its physician and postPost. We encourage the submission of original and previously unpublished work especially in the following areas: 1. Adaptive and co-evolutionary multimeme algorithms Genetics-Based Machine Learning:. On rare occasions, we may need to make unexpected changes to core modules; in this event we will contact offer holders as soon as possible to inform or consult them as appropriate. Terrence J.
Paraconsistency of Interactive Computation. In Ed. Denmark Harms, W. Information and Meaning in Evolutionary Processes. Cambridge: Cambridge University Press. Japaridze, G. Introduction to Computability Logic. Annals of Pure and Applied Logic, , Kornblith, H. Knowledge and its Place in Nature. Oxford: Oxford University Press. Lesne, A. Mathematical Structures in Computer Science, 17, Lloyd, S. New York: Alfred A Knopf. Maclennan, B. Theoretical Computer Science, , Maturana, H.
Autopoiesis and Cognition: the Realization of the Living. Boston: Reidel. The Society of Mind. New York: Simon and Schuster. Newell, A. Chess-playing Programs and the Problem of Complexity. IBM J. Quine, W Epistemology Naturalized. In Kornblith, H. The Expert Mind. Scientific American, August, Rozenberg, G.