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In this final chapter of the book we want to draw the main lines of the picture that has arisen in the previous chapters about the nature of scientific knowledge and its development, which was denoted as constructive realism. We start with a survey of the main conclusions thus far. In the remaining sections we will further articulate this particular epistemological position. Although this is the proper place for this articulation, detailed acquaintance with the foregoing Part IV is not strictly necessary. In this respect, Chapter 2 of Part I, Part II and Chapter 7 and 9 of Part III, and hence their main conclusions indicated below, are the most important ones.

Thus far it might seem that our conceptually relative point of departure leads to an extreme form of relativistic (nomic) realism. However, this would only be the case if we excluded constraints between the truths generated by different vocabularies for the same domain. In this chapter we will deal with the relation between an observational and a theoretical (cum observational) level, generated by an observational and an encompassing theoretical vocabulary for the same domain. Here the distinction between observational and theoretical components is, of course, assumed to be not of the classical, absolute form but of a sophisticated, relative kind. In particular, the distinction is supposed to reflect as much as possible what scientists consider as observable versus nonobservable/theoretical, including the fact that the distinction changes when theories are accepted and become observation theories. However, here we assume a temporarily fixed distinction. It will generate not only different kinds of (basic) truthlikeness, but also several relations between them.

In Chapter 2 we gave an exposition of HD-testing, the HD-method of testing hypotheses, with emphasis on the corresponding explication of confirmation. HD-testing attempts to give an answer to one of the questions one may be interested in, the truth question, which may be qualified according to the relevant epistemological position1. However, the (theory) realist, for instance, is not only interested in the truth question, but also in some other questions. To begin with, there is the more refined question of which (individual or general) facts2 the hypothesis explains (its explanatory successes) and with which facts it is in conflict (its failures), the success question for short. We will show in this chapter that the HD-method can also be used in such a way that it is functional for (partially) answering this question. This method is called HD-evaluation, and uses HD-testing. Since the realist ultimately aims to approach the strongest true hypothesis, if any, i.e., the (theoretical-cum-observa­tional) truth about the subject matter, the plausible third aim of the HD-method is to help answer the question of how far a hypothesis is from the truth, the truth approximation question. Here the truth will be taken in a relatively modest sense, viz., relative to a given domain and conceptual frame. In the next chapter we will make plausible and in Part III prove that HD-evaluation is also functional for answering the truth approximation question.

We will start by sketching in a systematic order the most important epistemological positions in the instrumentalism-realism debate, viz., instrumentalism, constructive empiricism, referential realism and theory realism. They will be ordered according to their answers to a number of leading questions, where every next question presupposes an affirmative answer to the foregoing one. The survey is restricted to the investigation of the natural world and hence to the natural sciences. It should be stressed that several complications arise if one wants to take the social and cultural world into account. However, the present survey may well function as a point of departure for discussing epistemological positions in the social sciences and the humanities.

Logic and philosophy of science have had many alliances since the rise of modern logic. The Wiener Kreis was even based on the idea of permanent cooperation. However, the ties have not yet culminated in a strong interdiscipline, as for instance logic and linguistics have in logical semantics. To be sure, logicians and philosophers of science feel they belong to the same family, as is for instance clear from the very happening of the 10th LMPS international congress. But, curiously enough, besides the section General Methodology, there is no section called Logical, or Formal, Methodology.

Leszek NOWAK: Foreword. GENERAL INTRODUCTION. Theo A.F. KUIPERS and Anne Ruth MACKOR: Cognitive Studies of Science and Common Sense. APPLIED SCIENCES. Henk ZANDVOORT: Concepts of Interdisciplinarity and Environmental Science. Rein VOS: The Logic and Epistemology of the Concept of Drug and Disease Profile. NATURAL SCIENCES. Rick C. LOOIJEN: On the Distinction Between Habitat and Niche, and Some Implications for Species' Differentiation. Gerben J. STAVENGA: Cognition, Irreversibility and the Direction of Time. Hinne HETTEMA and Theo A.F. KUIPERS: Sommerfeld's Atombau: A Case Study in Potential Truth Approximation. PSYCHOLOGICAL SCIENCES AND COMMON SENSE. Anne Ruth MACKOR: Intentional Psychology is a Biological Discipline. Jeanne PEIJNENBURG: Hempel's Rationality. On the Empty Nature of Being a Rational Agent. Lex GUICHARD: The Causal Efficacy of Propositional Attitudes. Michel ter HARK: Connectionism, Behaviourism and the Language of Thought. Alfons KEUPINK: Causal Modelling and Misspecification: Theory and Econometric Historical Practice. Maarten C.W. JANSSEN and Yao-Hua TAN: Default Reasoning and Some Applications in Economics. Bert HAMMINGA: Interesting Theorems in Economics. SCIENCE AND COMMON SENSE IN GENERAL. Renee DALITZ: Knowledge, Gender and Social Bias. Erik C.W. KRABBE: Can We Ever Pin One Down to a Formal Fallacy? Theo A.F. KUIPERS: Explicating the Falsificationist and Instrumentalist Methodology by Decomposing the Hypothetico-Deductive Method. Sjoerd D. ZWART: A Hidden Variable in the Discussion About 'Language Dependency' of Truthlikeness. Roberto FESTA: Verisimilitude, Disorder, and Optimum Prior Probabilities. About the Authors. Index of Names

Design research programs attempt to bring together the properties of available materials and the demands derived from intended applications. The logic of problem states and state transitions in such programs, including assessment criteria and heuristic principles, is described in settheoretic terms, starting with a naive model comprising an intended profile and the operational profile of a prototype. In a first concretization the useful distinction between structural and functional properties is built into the model. In two further concretizations the inclusion of potential applications is motivated and described for the case of drug research as well as the inclusion of potential realizations for the case of complex products. Next, another line of concretization of the naive model, the incorporation of potentially relevant properties, is sketched. Then the partial analogy between “product-” and “truth-approximation” is indicated. We conclude with some remarks about the usefulness of our models for products reaching the market in comparison to the the so-called social construction of technology approach.

A number of evaluations of the general prospects of Carnap's program of inductive logic have been presented on different occasions (e.g., Adler 1980, Jeffrey 1973, Kuipers 1984a, Lakatos 1968, Niiniluoto 1982). Niiniluoto's and my own account are the most positive about the internal strength of the program, provided one includes open systems of inductive probability, i.e., systems with non-zero probabilities for contingent universal generalizations. As is well-known, this was done for the first time by Hintikka.This paper will not add a new evaluation to the list. Instead, I will show that the internal heuristic of Carnap's restricted program is already strong enough to solve one of its major problems, i.e., the problem of integrating analogy influences in systems of inductive probability.Carnap has given considerable attention to the problem of analogy; to be precise, to what he called analogy by similarity, or analogy influences based on a distance function between the predicates.

1. Carnap's continuum of inductive methods for a family of monadic predicates, the so-called ?-continuum or ?-system, is restricted by the as sumption that the size of the family is known at the start of the learning process. In the proper inductive situation we do not have this information. In this article a two-dimensional system will be constructed that is appropriate to deal with the proper inductive situation. This system describes a learning process both for relative frequencies of properties and for the size of the family; it may therefore be called a generalization of Carnap's continuum.

Hintikka has defined a one-dimensional continuum of a priori probability distributions on constituents and has built on it a two-dimensional continuum of inductive methods with the aid of Carnap’s λ-continuum ([1]), which plays also a fundamental role in his continuum of a priori distributions, and the formula of Bayes ([2]). Here a two-dimensional continuum of a priori probability distributions will be introduced. On its base a three-dimensional continuum of inductive methods can be constructed in the same way as Hintikka has done. The importance of the new continuum of a priori distributions, which is also based on Carnap’s λ-continuum but in a completely different way, is that it leaves room for almost all kinds of a priori considerations, whereas Hintikka’s continuum admits only considerations that lead to increasing probability for the constituents by increasing size.

Carnap constructed the continuum of inductive methods (i.e., the set of C-systems, 0 < λ < ∞) for application to the sentences of a first-order language, containing a finite family of (Q —) predicates and a countable number of individual constants. Let K be such a family of Q-predicates Q1, Q2,… Q k . We consider first the case that there are only finitely many individual constants: U N = a1, a2, …, aN. Let U n indicate the set containing the first n individuals a1, a2, …, a n . A state-description of U n is a sentence of the form Q1 (a1 & Q i2 (a2) & … & Q in (an) and will be indicated here by e(U n ). The number of occurrences of Q i in e(U n ) will be indicated by n i (e(U n )), or simply n i .

One aim of methodological individualism in sociology is to explain social regularities on the basis of some regularity in the behaviour of individuals. An additional aim may be to explain such an individual regularity in turn on the basis of the assumption that the individuals intend to maximize expected utility, or at least that they behave as if they intend to do so. Explanations of social regularities exemplifying both features will here be called utilistic reduction.

In the first three sections of this chapter we formulate some technical problems which we have tried to solve in our research, but without success. All these problems may or may not have solutions of philosophical importance.

Modern inductive logic, conceived as a theory of inductive probabilities, is intended to be a useful instrument for learning from experience not only in objective contexts, where there is some underlying objective probability process, but also in other, non-objective contexts. However, for designing inductive systems, objective applications form the primary challenge, for they provide the objective, but unknown, goal which has to be approached in a rational way on the basis of increasing experimental evidence. Hence, in the following we will presuppose an underlying probability process, except when otherwise stated.

A number of authors have already tried to reconstruct general equilibrium theory (GET) in a structuralist way, in particular, following the order of appearance, Handler (1980), Balzer (1982), Haslinger (1983) and Hands (1985a). However, in view of their mutual criticism, see the papers referred to and in addition Balzer (1985) and Hands (1985b), this has thus far not led to a generally accepted reconstruction.

Carnap has always considered the problem of explication of rational (degree of) belief as the problem of the determination of the ‘logical probability’ of a hypothesis in the light of evidence (see, e.g., [2] and [7]). However, he does not make assumptions about the way in which evidence is obtained. More precisely, Carnap presupposes that the logical probability can be determined as soon as the non-logical constants of the language in which hypothesis and evidence are formulated are known. A consequence of this approach is that Carnap’s famous continuum of inductive methods for monadic predicate language (Carnap [3], see also Kemeny [21]) is a purely mathematical probability system presented in the form of a particular application.

This book is essentially restricted to expectation in a particular type of context. It is concerned with contexts corresponding to clear-cut countable scientific situations, i.e., countable situations in which the conceptualization of the relevant part of the world as well as the deductive interrelations are unproblematic. We call this type of context paradigmatic because it is often considered to represent the ideal or, at least, the simplest type of genuine scientific problem-situations. It does not seem, however, that such situations occur frequently in pure science nor that they constitute the most important universe of discourse for the philosophy of science. On the other hand one might argue that such situations occur frequently in practical affairs, such as applied sciences, and that they are therefore a topic of some interest for a general theory of the applied sciences.

In recent years some new work has appeared about the problem of inte? grating into systems of inductive probability analogy influences based on a distance function between the predicates, so-called analogy by similarity. Carnap's last (manuscript) attempts were published (Carnap (1980), Sec? tions 16 and 171), Niiniluoto (1981) formulated a weak and a strong 'meas? ure'. Spohn (1981) commented on them and has introduced a new pro? posal. None of these attempts seem to be very successful. Carnap restricts the discussion almost completely to 'sequences' of two predicates. As Spohn has pointed out, Niiniluoto's first measure violates positive instantial rel? evance and the second one violates Reichenbach's axiom. Both properties are certainly a prerequisite for inductive probability. In the second part of his paper, Spohn presented a system which has both properties and, in addition, it has regularity, initial symmetry between the predicates, some analogy influences and positive probabilities for contingent universal gen? eralizations. But Spohn is well aware that his system is not symmetric with respect to (the order of) individuals and, more importantly, that it is very ad hoc, because it lacks a plausible way of introduction or interpretation. There is also a paper by Costantini (1983) on the subject. We will com? ment on it in some detail in Section 3. In this paper we will explore the idea, briefly described on earlier oc? casions (e.g. Kuipers (1981), Section 3), that there are two quite different ways in which analogy (by similarity) influences can be conceived. The one, called instantial analogy, is based on the idea that predicates can 'acquire analogy' on the basis of evidence. This intuition plays the domi? nant role in most publications. The other, called existential analogy, is based on the idea that the distance between the predicates can play a role in the prior distribution. After a summary of the general background in Section 2 we will present