Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

Addressing both collegiate and professional sports, the updated edition of Fair Play explores the ethical presuppositions of competitive athletics and their ...

What can reason do for us and what can't it do? This is the question examined by Herbert A. Simon, who received the 1978 Nobel Prize in Economic Sciences "for his pioneering work on decision-making processes in economic organizations." The ability to apply reason to the choice of actions is supposed to be one of the defining characteristics of our species. In the first two chapters, the author explores the nature and limits of human reason, comparing and evaluating the major (...) theoretical frameworks that have been erected to explain reasoning processes. He also discusses the interaction of thinking and emotion in the choice of our actions. In the third and final chapter, the author applies the theory of bounded rationality to social institutions and human behavior, and points out the problems created by limited attention span human inability to deal with more than one difficult problem at a time. He concludes that we must recognize the limitations on our capabilities for rational choice and pursue goals that, in their tentativeness and flexibility, are compatible with those limits. (shrink)

Addressing both collegiate and professional sports, the updated edition of Fair Play: The Ethics of Sport explores the ethical presuppositions of competitive athletics and their connection both to ethical theory and to concrete moral dilemmas that arise in actual athletic competition. This fourth edition has been updated with new examples, including a discussion of Spygate by the New England Patriots and recent discoveries on the use of performance enhancing drugs by top athletes. Two additional authors, Cesar R. Torres and Peter (...) F. Hager, bring to this edition a discussion of the moral issues involved in youth sports and the ethics of being a fan, as well as a fresh perspective on the theories of broad internalism and the quest for excellence. Furthermore, major criticisms of broad internalism by philosophers William J. Morgan and Scott Kretchmar add a new dimension to the discussion on the moral foundations of winning. (shrink)

I argue that there can be no such thing as a borderline case of the predicate ‘phenomenally conscious’: for any given creature at any given time, it cannot be vague whether that creature is phenomenally conscious at that time. I first defend the Positive Characterization Thesis, which says that for any borderline case of any predicate there is a positive characterization of that case that can show any sufficiently competent speaker what makes it a borderline case. I then appeal to (...) the familiar claim that zombies are conceivable, and I argue that this claim entails that there can be no positive characterizations of borderline cases of ‘phenomenally conscious’. By the Positive Characterization Thesis, it follows that ‘phenomenally conscious’ can not have any borderline cases. (shrink)

Cognitive science is, of course, not really a new discipline, but a recognition of a fundamental set of common concerns shared by the disciplines of psychology, computer science, linguistics, economics, epistemology, and the social sciences generally. All of these disciplines are concerned with information processing systems, and all of them are concerned with systems that are adaptive—that are what they are from being ground between the nether millstone of their physiology or hardware, as the case may be, and the upper (...) millstone of a complex environment in which they exist. Systems that are adaptive may equally well be described as “artificial,” for as environments change, they can be expected to change too, as though they were deliberately designed to fit those environments (as indeed they sometimes are).The task of empirical science is to discover and verify invariants in the phenomena under study. The artificiality of information processing systems creates a subtle problem in defining empirical invariants in such systems. For observed regularities are very likely invariant only within a limited range of variation in their environments, and any accurate statement of the laws of such systems must contain reference to their relativity to environmental features. It is a common experience in experimental psychology, for example, to discover that we are studying sociology—the effects of the past histories of our subjects—when we think we are studying physiology—the effects of properties of the human nervous system. Similarly, business cycle economists are only now becoming aware of the extent to which the parameters of the system they are studying are dependent on the experiences of a population with economic events over the previous generation.In artificial sciences, the descriptive and the normative are never far apart. Thus, in economics, the “principle of rationality” is sometimes asserted as a descriptive invariant, sometimes as advice to decision makers. Similarly, in psychology, the processes of adaptation (learning) have always been a central topic, at one time a topic that dominated the whole field of research. Linguistics, too, has suffered its confusions between descriptive and normative attitudes towards its subject. But we must avoid the error, in studying information processing systems, of thinking that the adaptive processes themselves must be invariant; and we must be prepared to face the complexities of regression in the possibility that they themselves may be subject to improvement and adaptation.It might have been necessary a decade ago to argue for the commonality of the information processes that are employed by such disparate systems as computers and human nervous systems. The evidence for that commonality is now overwhelming, and the remaining questions about the boundaries of cognitive science have more to do with whether there also exist nontrivial commonalities with information processing in genetic systems than with whether men and machines both think. (shrink)

_The_ _Routledge Companion to Philosophy of Medicine _is a comprehensive guide to topics in the fields of epistemology and metaphysics of medicine. It examines traditional topics such as the concept of disease, causality in medicine, the epistemology of the randomized controlled trial, the biopsychosocial model, explanation, clinical judgment and phenomenology of medicine and emerging topics, such as philosophy of epidemiology, measuring harms, the concept of disability, nursing perspectives, race and gender, the metaphysics of Chinese medicine, and narrative medicine. Each of (...) the 48 chapters is written especially for this volume and with a student audience in mind. For pedagogy and clarity, each chapter contains an extended example illustrating the ideas discussed. This text is intended for use as a reference for students in courses in philosophy of medicine and philosophy of science, and pairs well with _The_ _Routledge Companion to Bioethics_ for use in medical humanities and social science courses. (shrink)

Hans Krebs' discovery, in 1932, of the urea cycle was a major event in biochemistry. This article describes a program, KEKADA, which models the heuristics Hans Krebs used in this discovery. KEKADA reacts to surprises, formulates explanations, and carries out experiments in the same manner as the evidence in the form of laboratory notebooks and interviews indicates Hans Krebs did. Furthermore, we answer a number of questions about the nature of the heuristics used by Krebs, in particular: How domain‐specific are (...) the heuristics? To what extent are they idiosyncratic to Krebs? To what extent do they represent general strategies of problem‐solving search?The relative generality of KEKADA allows us to view the control structure of KEKADA and its domain‐independent heuristics as a model of scientific experimentation that should apply over a broad domain. (shrink)

We describe a set of two computer‐implemented models that solve physics problems in ways characteristic of more and less competent human solvers. The main features accounting for different competences are differences in strategy for selecting physics principles, and differences in the degree of automation in the process of applying a single principle. The models provide a good account of the order in which principles are applied by human solvers working problems in kinematics and dynamics. They also are sufficiently flexible to (...) allow easy extension to several related domains of physics problems. (shrink)

In recent years, a number of theorists have claimed that beliefs about probability are transparent. To believe probably p is simply to have a high credence that p. In this paper, I prove a variety of triviality results for theses like the above. I show that such claims are inconsistent with the thesis that probabilistic modal sentences have propositions or sets of worlds as their meaning. Then I consider the extent to which a dynamic semantics for probabilistic modals can capture (...) theses connecting belief, certainty, credence, and probability. I show that although a dynamic semantics for probabilistic modals does allow one to validate such theses, it can only do so at a cost. I prove that such theses can only be valid if probabilistic modals do not satisfy the axioms of the probability calculus. (shrink)

Cognitive science is, of course, not really a new discipline, but a recognition of a fundamental set of common concerns shared by the disciplines of psychology, computer science, linguistics, economics, epistemology, and the social sciences generally. All of these disciplines are concerned with information processing systems, and all of them are concerned with systems that are adaptive—that are what they are from being ground between the nether millstone of their physiology or hardware, as the case may be, and the upper (...) millstone of a complex environment in which they exist. Systems that are adaptive may equally well be described as “artificial,” for as environments change, they can be expected to change too, as though they were deliberately designed to fit those environments (as indeed they sometimes are).The task of empirical science is to discover and verify invariants in the phenomena under study. The artificiality of information processing systems creates a subtle problem in defining empirical invariants in such systems. For observed regularities are very likely invariant only within a limited range of variation in their environments, and any accurate statement of the laws of such systems must contain reference to their relativity to environmental features. It is a common experience in experimental psychology, for example, to discover that we are studying sociology—the effects of the past histories of our subjects—when we think we are studying physiology—the effects of properties of the human nervous system. Similarly, business cycle economists are only now becoming aware of the extent to which the parameters of the system they are studying are dependent on the experiences of a population with economic events over the previous generation.In artificial sciences, the descriptive and the normative are never far apart. Thus, in economics, the “principle of rationality” is sometimes asserted as a descriptive invariant, sometimes as advice to decision makers. Similarly, in psychology, the processes of adaptation (learning) have always been a central topic, at one time a topic that dominated the whole field of research. Linguistics, too, has suffered its confusions between descriptive and normative attitudes towards its subject. But we must avoid the error, in studying information processing systems, of thinking that the adaptive processes themselves must be invariant; and we must be prepared to face the complexities of regression in the possibility that they themselves may be subject to improvement and adaptation.It might have been necessary a decade ago to argue for the commonality of the information processes that are employed by such disparate systems as computers and human nervous systems. The evidence for that commonality is now overwhelming, and the remaining questions about the boundaries of cognitive science have more to do with whether there also exist nontrivial commonalities with information processing in genetic systems than with whether men and machines both think. (shrink)

We study one way in which stable phenomena can exist in an NIP theory. We start by defining a notion of ‘pure instability’ that we call ‘distality’ in which no such phenomenon occurs. O-minimal theories and the p-adics for example are distal. Next, we try to understand what happens when distality fails. Given a type p over a sufficiently saturated model, we extract, in some sense, the stable part of p and define a notion of stable independence which is implied (...) by non-forking and has bounded weight. (shrink)

Fourteen subjects were tape‐recorded while they undertook to find a law to summarize numerical data they were given. The source of the data was not identified, nor were the variables labeled semantically. Unknown to the subjects, the data were measurements of the distances of the planets from the sun and the periods of their revolutions about it—equivalent to the data used by Johannes Kepler to discover his third law of planetary motion.Four of the 14 subjects discovered the same law as (...) Kepler did (the period varies as the 3/2 power of the distance), and a fifth came very close to the answer. The subiects' protocols provide a detailed picture of the problem‐solving searches they engaged in, which were mainly, but not exclusively, in the space of possible functions for fitting the data, and provide explanations as to why some succeeded and the others failed.The search heuristics used by the subjects are similar to those embodied in the BACON program, computer simulation of certain scientific discovery processes. The experiment demonstrates the feasibility of examining some of the processes of scientific discovery by recreating, in the laboratory, discovery situations of substantial historical relevance. It demonstrates also, that under conditions rather similar to those of the original discoverer, a law can be rediscovered by persons of ordinary intelligence (i.e., the intelligence needed for academic success in a good university). The data for the successful subjects reveal no “creative” processes in this kind of a discovery situation different from those that are regularly observed in all kinds of problem‐solving settings. (shrink)

It is often claimed that there can be no such thing as a logic of scientific discovery, but only a logic of verification. By 'logic of discovery' is usually meant a normative theory of discovery processes. The claim that such a normative theory is impossible is shown to be incorrect; and two examples are provided of domains where formal processes of varying efficacy for discovering lawfulness can be constructed and compared. The analysis shows how one can treat operationally and formally (...) phenomena that have usually been dismissed with fuzzy labels like 'intuition' and 'creativity'. (shrink)

In this paper I use philosophical accounts on the relationship between trust and knowledge in science to apprehend this relationship on the Web. I argue that trust and knowledge are fundamentally entangled in our epistemic practices. Yet despite this fundamental entanglement, we do not trust blindly. Instead we make use of knowledge to rationally place or withdraw trust. We use knowledge about the sources of epistemic content as well as general background knowledge to assess epistemic claims. Hence, although we may (...) have a default to trust, we remain and should remain epistemically vigilant; we look out and need to look out for signs of insincerity and dishonesty in our attempts to know. A fundamental requirement for such vigilance is transparency: in order to critically assess epistemic agents, content and processes, we need to be able to access and address them. On the Web, this request for transparency becomes particularly pressing if (a) trust is placed in unknown human epistemic agents and (b) if it is placed in non-human agents, such as algorithms. I give examples of the entanglement between knowledge and trust on the Web and draw conclusions about the forms of transparency needed in such systems to support epistemically vigilant behaviour, which empowers users to become responsible and accountable knowers. (shrink)

We show basic facts about dp-minimal ordered structures. The main results are: dp-minimal groups are abelian-by-finite-exponent, in a divisible ordered dp-minimal group, any infinite set has non-empty interior, and any theory of pure tree is dp-minimal.

Humans can recollect past events in details and/or know that an object, person, or place has been encountered before. During the last two decades, there has been intense debate about how recollection and familiarity are organized in the brain. Here, we propose an integrative memory model which describes the distributed and interactive neurocognitive architecture of representations and operations underlying recollection and familiarity. In this architecture, the subjective experience of recollection and familiarity arises from the interaction between core systems and an (...) attribution system. By integrating principles from current theoretical views about memory functioning, we provide a testable framework to refine the prediction of deficient versus preserved mechanisms in memory-impaired populations. The case of Alzheimer's disease is considered as an example because it entails progressive lesions starting with limited damage to core systems before invading step-by-step most parts of the model-related network. We suggest a chronological scheme of cognitive impairments along the course of AD, where the inaugurating deficit would relate early neurodegeneration of the perirhinal/anterolateral entorhinal cortex to impaired familiarity for items that need to be discriminated as viewpoint-invariant conjunctive entities. The integrative memory model can guide future neuropsychological and neuroimaging studies aiming to understand how such a network allows humans to remember past events, to project into the future, and possibly also to share experiences. (shrink)

Generative Artificial Intelligence (GenAI), such as ChatGPT, shows great promise and potential and is gradually being used in mental health care, but it also raises ethical concerns. These relate t...

Language maps signals onto meanings through the use of two distinct types of structure. First, the space of meanings is discretized into categories that are shared by all users of the language. Second, the signals employed by the language are compositional: The meaning of the whole is a function of its parts and the way in which those parts are combined. In three iterated learning experiments using a vast, continuous, open-ended meaning space, we explore the conditions under which both structured (...) categories and structured signals emerge ex nihilo. While previous experiments have been limited to either categorical structure in meanings or compositional structure in signals, these experiments demonstrate that when the meaning space lacks clear preexisting boundaries, more subtle morphological structure that lacks straightforward compositionality—as found in natural languages—may evolve as a solution to joint pressures from learning and communication. (shrink)

For many years, the game of chess has provided an invaluable task environment for research on cognition, in particular on the differences between novices and experts and the learning that removes these differences, and upon the structure of human memory and its paramaters. The template theory presented by Gobet and Simon based on the EPAM theory offers precise predictions on cognitive processes during the presentation and recall of chess positions. This article describes the behavior of CHREST, a computer implementation of (...) the template theory, in a memory task when the presentation time is varied from one second to sixty, on the recall of game and random positions, and compares the model to human data. Strong players are better than weak players in both types of positions, especially with long presentation times, but even after brief presentations. CHREST predicts the data, both qualitatively and quantitatively. Strong players' superiority with random positions is explained by the large number of chunks they hold in LTM. Their excellent recall with short presentation times is explained by templates, a special class of chunks. CHREST is compared to other theories of chess skill, which either cannot account for the superiority of Masters in random positions or predict too strong a performance of Masters in such positions. (shrink)

This paper is a fresh attempt to articulate the role of a theory of truthmakers. We argue that truthmaker theory constitutes a cornerstone of good methodology in metaphysics, but that a conflation of truthmaker theory with the theory of truth has been responsible for certain excesses associated with truthmaker-based approaches in the recent literature. If truthmaker theory is not a component of a theory of truth, then truthmaker maximalism – the view that every truth has a truthmaker – loses its (...) primary motivation. More generally, if the task of truthmaker theory is not to provide a definition or account of truth in truthmaker terms, there is no pressing need for hard, a priori principles stating which truths have truthmakers and which do not. (shrink)

Trust is pervasive in our lives. Both our simplest actions--like buying a coffee, or crossing the street--as well as the functions of large collective institutions--like those of corporations and nation states--wouldn't be possible without it. Yet, only in the last several decades has trust started to receive focused attention from philosophers as a specific topic of investigation. The Routledge Handbook of Trust and Philosophybrings together XX never before published essays, accessible for both students and researchers, created to cover the most (...) salient topics in the various theories of trust. The Handbookis broken up into four sections: a first on basic foundational and conceptual issues; a second on when trust is warranted; a third on the epistemology of trust; and a fourth on trust and science and technology. Each section is preceded by a short introduction, and each chapter includes a bibliography and cross-references to other entries in the volume. (shrink)