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  ISEM COURSES

For  Whom  Isem?

For managers, communicators and philosophers who have to think, live and making choices in a world that the new scientific and technological scenarios has more and more shaped in depth;

For young scientists who wants a training making them able to face the new inter and trans-disciplinary challenges of research.

Master “Paul K. Feyerabend”

 

  • Towards an Epistemology of Complexity

 Epistemology evolution in perspective: from “external” normative discourse on science practice to “discipline”, through the “political” critique of science. To the left and to the right of Popper.

  • Information, Complexity and Systems

The problem of mono-disciplinary reductionism. From Sets to Systems. A Science speaking of Science,Wiener & Co. – the problem of falsisfiability of methodological approaches.

  • Knowledge Production Models

Crossing: Mono, Multi, Inter, Trans disciplinary. The Observer Role in Science.

  • Systemic Openness

Systemic Models based on Thermodinamic and Logical Openness. Isomorphic Models and Theories. Hierarchies of Models.

  • Dynamic Usage of Models (DYSAM)

The model choosing problem between “theory” and “phenomenology”. Knowledge Production, objectivism, constructivism. Fuzzy Maps.

  • Computational Models and Intrinsic Emergence

Knowledge as irreducible “novelty”- Simulation and toy-worlds – The Observer asEemergence Detector. Emergence and Collective Phenomena.

  • Systems of Knowledge Production and Ethics

Values, Evaluations and Ethic balance as Growth and Development factor. Knowledge in Post-industrial Society.

  • Collective Intelligence

Science in the Age of Internet, New Production Processes and Science communication. Online Reviews. The ArXiv case.

  • Laboratory and the competence sharing problem.

From Gottinga to Los Alamos – The Big Science – the University historical role – The CNR model. The Santa Fè experience.

THEORETICAL TOOLS FOR A SYSTEMIC EPISTEMOLOGY

  • Formal Languages, Automata and Models.
  • Classical Turing-Computation Theory
  • Theory of Dynamical Systems
  • Quantum Formalisms, Complex Systems and Fuzziness
  • Classical Science: objectivism, riductionism and causality
  • General Principles of Systemics
  • The Classical notion of Emergence and causal objectivism
  • Emergence and Self-Organization: Cellular Automata, Artrificial Life, AlChemy (Artificial Chemistry), Genetic Algorithms, Strong AI, Dissipative Systems, Synergetics, Connectionisn and Neural Nets, Distinctions, HyperStructure, Logical Openness, Quantum Systemics.
  • Cognitive Processes and Connectionist Psychology
  • Knowledge engineerings

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Credits: apnetwork.it