Concepts and problems; The calculus of inductive probability; Alternative inductive logics and the justification of induction; Probability and action; The pragmatic theory of inductive probability; The logic of causal statements as a formal language; The logic of causal statements as a model of natural language; The dispositional theory of empirical probability; Cause and chance in space - time systems; The presupposition of theory induction; Chance, cause, and reason.
In this paper I synthesize a unified system out of Peirce's life work, and name it Peirce's Evolutionary Pragmatic Idealism. Peirce developed this philosophy in four stages: His 1868–69 theory that cognition is a continuous and infinite social semiotic process, in which Man is a sign. His Popular Science Monthly pragmatism and frequency theory of probabilistic induction. His 1891–93 cosmic evolutionism of Tychism, Synechism, and Agapism. Pragmaticism: The doctrine of real potentialities, and Peirce's pragmatic program for developing concrete reasonableness. Peirce's (...) evolutionary conception of the cosmos is pantheistic, and he constructed it to reconcile religion with Darwinian evolution. (shrink)
This general type of view may be characterized more fully by using the notion of an inductive method. All scientists use approximately the same inductive method, which we will call the standard inductive method. This method is based on the rule of induction by simple enumeration, which may be roughly stated as follows: if it is known only that a certain property Ψ has accompanied another property Φ in a number of instances, then the larger this number of instances the (...) higher the probability that the next occurrence of Φ will be accompanied by Ψ. Though scientists actually reason inductively in accord with this rule, it is important that there are logically consistent inductive methods based on alternative rules. We will describe two of these briefly. The inverse inductive method assigns probabilities according to the rule that if it is known only that Ψ has accompanied Φ a number of times, then the larger the number of instances the lower the probability that the next occurrence of Φ will be accompanied by Ψ. The random predictive method assigns to the proposition that the next occurrence of Φ will be accompanied by Ψ a probability completely independent of the number of times that Ψ has accompanied Φ in the past.. (shrink)
But even with respect to inductive arguments there are a number of different philosophical problems. One is to make explicit the fundamental or most general pattern or patterns of inductive argument. Once these patterns are known a second and third problem arise. The second is to justify man's use of and faith in inductive arguments. And the third is to formulate some general propositions about nature which could reasonably be accepted by users of inductive arguments and which when added to (...) the premises of these arguments make them explicitly deductive. (shrink)
We distinguish scanning switches, which only enumerate states, from function switches which transform input states into output states. For the latter we introduce a logical network symbolism. Our history of early computer switching begins with the suggestions of Ramon Lull and Gottfried Leibniz, surveys the evolution of mechanical scanning switches and the first mechanical function switches, and then describes the first electromechanical function switches. The main themes of the present paper are that William S. Jevons built the first substantial function (...) switch (his logical piano), and that his work led to the design by Allan Marquand of the first substantial electromechanical function switch, as well as to Charles S. Peirce's idea for an electrical general-purpose programmable computer. These events all occurred fifty years before the first general-purpose programmable computers were constructed (in the 1940's), but they had no influence. (shrink)
The definition of “model of a system” in terms of a homomorphism of the states of the system is evaluated and an alternative definition in terms of sequence generators is proposed. Sequence generators are finite graphs whose points represent complete states of a system. Sequence generators include finite automata and other information processing systems as special cases. It is shown how to define models in terms of a projection operator which applies to any sequence generator which has an output projection (...) and yields a new sequence generator. A model produced by the projection operator is embedded in the system it models. The notion of embedding is discussed informally and some questions raised about the relations of deterministic, indeterministic, and probabilistic models and systems. (shrink)