Tag Archives: Information Theory

Pragmatic Traction • 5

Posted on September 28, 2017 by Jon Awbrey

☯   TAO   ☯ Trials And Outcomes Expression | Impression Effectors | Receptors Exertion | Reaction Conduct | Bearing Control | Observe Effect | Detect Poke | Peek Note | Note Pat | Apt | Tap Pragmatism makes thinking … Continue reading →

Posted in Abduction, C.S. Peirce, Control, Cybernetics, Deduction, Error, Error-Controlled Regulation, Feedback, Fixation of Belief, Hypothesis, Induction, Inference, Information, Information Theory, Inquiry, Inquiry Driven Systems, Knowledge, Knowledge Representation, Learning, Learning Theory, Likelihood, Logic, Logic of Science, Logical Graphs, Peirce, Philosophy, Philosophy of Science, Pragmatic Information, Pragmatic Maxim, Pragmatism, Probability, Probable Reasoning, Scientific Inquiry, Scientific Method, Semiotics, Statistical Inference, Statistics, Uncertainty, Volition | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Pragmatic Traction • 4

Posted on September 27, 2017 by Jon Awbrey

Re: Oliver Maclaren • Statistics Without True Models Or Hypothesis Testing I once wrote a “pure empiricist” sequential learning program that took this sort of approach to the data in its input stream. Here is the manual, that will give … Continue reading →

Posted in Abduction, C.S. Peirce, Control, Cybernetics, Deduction, Error, Error-Controlled Regulation, Feedback, Fixation of Belief, Hypothesis, Induction, Inference, Information, Information Theory, Inquiry, Inquiry Driven Systems, Knowledge, Knowledge Representation, Learning, Learning Theory, Likelihood, Logic, Logic of Science, Logical Graphs, Peirce, Philosophy, Philosophy of Science, Pragmatic Information, Pragmatic Maxim, Pragmatism, Probability, Probable Reasoning, Scientific Inquiry, Scientific Method, Semiotics, Statistical Inference, Statistics, Uncertainty | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Pragmatic Traction • 3

Posted on September 25, 2017 by Jon Awbrey

Re: Deborah G. Mayo • Revisiting Popper’s Demarcation of Science I think Peirce would say that any struggle to pass from the irritation of doubt toward the settlement of belief is a form of inquiry — it’s just that some … Continue reading →

Posted in Abduction, C.S. Peirce, Control, Cybernetics, Deborah G. Mayo, Deduction, Error, Error-Controlled Regulation, Feedback, Fixation of Belief, Hypothesis, Induction, Inference, Information, Information Theory, Inquiry, Inquiry Driven Systems, Knowledge, Knowledge Representation, Learning, Learning Theory, Likelihood, Logic, Logic of Science, Peirce, Philosophy, Philosophy of Science, Pragmatic Information, Pragmatic Maxim, Pragmatism, Probability, Probable Reasoning, Scientific Inquiry, Scientific Method, Semiotics, Statistical Inference, Statistics, Uncertainty | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Pragmatic Traction • 2

Posted on September 16, 2017 by Jon Awbrey

Re: FB | Ecology of Systems Thinking • Richard Saunders I’m about to be diverted for a couple of weeks but this is an ever-ongoing question so I know I’ll be coming back to it again.  The short shrift goes … Continue reading →

Posted in Abduction, C.S. Peirce, Control, Cybernetics, Deborah G. Mayo, Deduction, Error, Error-Controlled Regulation, Feedback, Fixation of Belief, Hypothesis, Induction, Inference, Information, Information Theory, Inquiry, Inquiry Driven Systems, Knowledge, Knowledge Representation, Learning, Learning Theory, Likelihood, Logic, Logic of Science, Peirce, Philosophy, Philosophy of Science, Pragmatic Information, Pragmatic Maxim, Pragmatism, Probability, Probable Reasoning, Scientific Inquiry, Scientific Method, Semiotics, Statistical Inference, Statistics, Uncertainty | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Pragmatic Traction • 1

Posted on September 14, 2017 by Jon Awbrey

Re: Deborah G. Mayo • Peircean Induction and the Error-Correcting Thesis C.S. Peirce’s pragmatic maxim marks the place where the tire of theory meets the test track of experience — it tells us how general ideas are impacted by practical … Continue reading →

Posted in Abduction, C.S. Peirce, Control, Cybernetics, Deborah G. Mayo, Deduction, Error, Error-Controlled Regulation, Feedback, Fixation of Belief, Hypothesis, Induction, Inference, Information, Information Theory, Inquiry, Inquiry Driven Systems, Knowledge, Knowledge Representation, Learning, Learning Theory, Likelihood, Logic, Logic of Science, Peirce, Philosophy, Philosophy of Science, Pragmatic Information, Pragmatic Maxim, Pragmatism, Probability, Probable Reasoning, Scientific Inquiry, Scientific Method, Semiotics, Statistical Inference, Statistics, Uncertainty | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Survey of Semiotic Theory Of Information • 2

Posted on February 27, 2017 by Jon Awbrey

This is a Survey of previous blog and wiki posts on the Semiotic Theory Of Information.  All my projects are exploratory in essence but this line of inquiry is more open-ended than most.  The question is: What is information and how … Continue reading →

Posted in Abduction, C.S. Peirce, Communication, Control, Cybernetics, Deduction, Determination, Discovery, Doubt, Epistemology, Fixation of Belief, Induction, Information, Information = Comprehension × Extension, Information Theory, Inquiry, Inquiry Driven Systems, Inquiry Into Inquiry, Interpretation, Invention, Knowledge, Learning Theory, Logic, Logic of Relatives, Logic of Science, Mathematics, Peirce, Philosophy, Philosophy of Science, Pragmatic Information, Probable Reasoning, Process Thinking, Relation Theory, Scientific Inquiry, Scientific Method, Semeiosis, Semiosis, Semiotic Information, Semiotics, Sign Relational Manifolds, Sign Relations, Surveys, Triadic Relations, Uncertainty | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | 1 Comment

Homunculomorphisms • 2

Posted on February 12, 2016 by Jon Awbrey

Re: John Baez • The Internal Model Principle There’s a far-ranging discussion that takes off from this point, touching on links among analogical reasoning, arrows and functors, cybernetic images, iconic versus symbolic representations, mental models, systems simulations, etc., and just … Continue reading →

Posted in Analogy, Ashby, Automata, Control Systems, Cybernetics, Homunculi, Homunculomorphisms, Iconicity, Information Theory, Inquiry, Inquiry Driven Systems, Intentionality, Internal Models, Logic, Logic of Science, Mathematics, Mental Models, Model Theory, Optimal Control, Peirce, Semiotics, Systems Theory, Triadic Relations | Tagged , , , , , , , , , , , , , , , , , , , , , , | 1 Comment

Homunculomorphisms • 1

Posted on February 11, 2016 by Jon Awbrey

Re: John Baez • The Internal Model Principle Ashby’s book was my own first introduction to cybernetics and I recently returned to his discussion of regulation games in connection with some issues in Peirce’s theory of inquiry. In that context … Continue reading →

Posted in Ashby, Automata, Category Theory, Control, Control Systems, Control Theory, Cybernetics, Homunculi, Homunculomorphisms, Information, Information Theory, Inquiry, Inquiry Driven Systems, Intentionality, Internal Models, Logic of Science, Mathematics, Mental Models, Optimal Control, Peirce, Systems Theory, Triadic Relations | Tagged , , , , , , , , , , , , , , , , , , , , , | 1 Comment

Inquiry, Signs, Relations • 1

Posted on July 5, 2015 by Jon Awbrey

Re: Michael Harris • A Non-Logical Cognitive Phenomenon Human spontaneous non-demonstrative inference is not, overall, a logical process.  Hypothesis formation involves the use of deductive rules, but is not totally governed by them;  hypothesis confirmation is a non-logical cognitive phenomenon:  … Continue reading →

Posted in Abduction, Action, Analogy, C.S. Peirce, Cognition, Cognitive Science, Communication, Deduction, Foundations of Mathematics, Induction, Information, Information Theory, Inquiry, Inquiry Into Inquiry, Interpretation, Logic, Logic of Relatives, Logic of Science, Mathematics, Michael Harris, Peirce, Philosophy, Philosophy of Mathematics, Philosophy of Science, Pragmatism, Relation Theory, Relevance, Semiotics, Sign Relations, Triadic Relations | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Survey of Semiotic Theory Of Information • 1

Posted on May 17, 2015 by Jon Awbrey

This is a Survey of previous blog and wiki posts on the Semiotic Theory Of Information.  All my projects are exploratory in essence but this line of inquiry is more open-ended than most.  The question is: What is information and how … Continue reading →

Posted in Abduction, C.S. Peirce, Communication, Control, Cybernetics, Deduction, Determination, Discovery, Doubt, Epistemology, Fixation of Belief, Induction, Information, Information = Comprehension × Extension, Information Theory, Inquiry, Inquiry Driven Systems, Inquiry Into Inquiry, Interpretation, Invention, Knowledge, Learning Theory, Logic, Logic of Relatives, Logic of Science, Mathematics, Peirce, Philosophy, Philosophy of Science, Pragmatic Information, Probable Reasoning, Process Thinking, Relation Theory, Scientific Inquiry, Scientific Method, Semeiosis, Semiosis, Semiotic Information, Semiotics, Sign Relational Manifolds, Sign Relations, Surveys, Triadic Relations, Uncertainty | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment