Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty —a property of listeners' prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly through exposure. Using (...) probability estimates from an unsupervised, variable-order Markov model, 12 melodic contexts high in entropy and 12 melodic contexts low in entropy were selected from two musical repertoires differing in structural complexity (simple and complex). Musicians and non-musicians listened to the stimuli and provided explicit judgments of perceived uncertainty (explicit uncertainty). We also examined an indirect measure of uncertainty computed as the entropy of expectedness distributions obtained using a classical probe-tone paradigm where listeners rated the perceived expectedness of the final note in a melodic sequence (inferred uncertainty). Finally, we simulate listeners' perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models in the literature. The results show that listeners experience greater uncertainty in high-entropy musical contexts than low-entropy contexts. This effect is particularly apparent for inferred uncertainty and is stronger in musicians than non-musicians. Consistent with the Statistical Learning Hypothesis, the results suggest that increased domain-relevant training is associated with an increasingly accurate cognitive model of probabilistic structure in music. (shrink)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

Localizing content in neural networks provides a bridge to understanding the way in which the brain stores and processes information. In this paper, I propose the existence of polytopes in the state space of the hidden layer of feedforward neural networks as vehicles of content. I analyze these geometrical structures from an information-theoretic point of view, invoking mutual information to help define the content stored within them. I establish how this proposal addresses the problem of misclassification and provide a novel (...) solution to the disjunction problem, which hinges on the precise nature of the causal-informational framework for content advocated herein. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the nature (...) of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

First, I offer a short overview on the classical occidental philosophy as propounded by the ancient Greeks and the natural philosophies of the last 2000 years until the dawn of the empiricist logic of science in the twentieth century, which wanted to delimitate classical metaphysics from empirical sciences. In contrast to metaphysical concepts which didn’t reflect on the language with which they tried to explain the whole realm of entities empiricist logic of science initiated the end of metaphysical theories by (...) reflecting on the preconditions for foundation and justification of sentences about objects of investigation, i.e. a coherent definition of language in general, which was not the aim of classical metaphysics. Unexpectedly empiricist logic of science in the linguistic turn failed in the physical and mathematical reductionism of language and its use in communication, as will be discussed below in further detail. Nevertheless, such reflection on language and communication also introduced this vocabulary into biology. Manfred Eigen and bioinformatics, later on biolinguistics, used ‘language’ applied linguistic turn thinking to biology coherent to the logic of science and its formalisable aims. This changed significantly with the birth of biosemiotics and biohermeneutics. At the end of this introduction it will be outlined why and how all these approaches reproduced the deficiencies of the logic of science and why the biocommunicative approach avoids their abstractive fallacies. (shrink)

The monitoring role performed by the board of directors is an important corporate governance control mechanism, especially in countries where external mechanisms are less well developed. The gender composition of the board can affect the quality of this monitoring role and thus the financial performance of the firm. This is part of the “business case” for female participation on boards, though arguments may also be framed in terms of ethical considerations. While the issue of board gender diversity has attracted growing (...) research interest in recent years, most empirical results are based on U.S. data. This article adds to a growing number of non-U.S. studies by investigating the link between the gender diversity of the board and firm financial performance in Spain, a country which historically has had minimal female participation in the workforce, but which has now introduced legislation to improve equality of opportunities. We investigate the topic using panel data analysis and find that gender diversity – as measured by the percentage of women on the board and by the Blau and Shannon indices – has a positive effect on firm value and that the opposite causal relationship is not significant. Our study suggests that investors in Spain do not penalise firms which increase their female board membership and that greater gender diversity may generate economic gains. (shrink)

Although the concept of uncertainty is as old as Epicurus’s writings, and an excellent quantitative theory, with entropy as the measure of uncertainty having been developed in recent times, there has been little exploration of the qualitative theory. The purpose of the present paper is to give a qualitative axiomatization of uncertainty, in the spirit of the many studies of qualitative comparative probability. The qualitative axioms are fundamentally about the uncertainty of a partition of the probability space of events. Of (...) course, it is common to speak of the uncertainty, or randomness, of a random variable, but only the partition defined by the values of the random variable enter into the definition of uncertainty, not the actual values. It is straightforward to add axioms for decision making following the general line of Savage from the 1950s. Indeed, in the spirit of Epicurus, it is really our intuitive feeling about the uncertainty of the future that motivates much of our thinking about decisions. Here, the distinction between the concepts of probability and uncertainty can be made by citing many familiar examples. Without spelling out the technical details, the axiomatization of qualitative probability with uncertainty as the most important primitive concept, it is possible to raise a different kind of question about bounded rationality. This new question is whether or not one should bound the uncertainty in thinking and investigating any detailed framework of decision making. Discussion of this point is certainly different from the question of bounding rationality by not maximizing expected utility. In practice, we naturally bound uncertainty in our analysis of decision-making problems. As in the case of formulating an alternative for maximizing expected utility, so is the case of rational alternatives to maximizing uncertainty. There are several issues to consider. In the spirit of my other work in qualitative probability, I explore alternatives rather than attempt to give a definitive argument for one single solution. (shrink)

Several authors have argued that causes differ in the degree to which they are ‘specific’ to their effects. Woodward has used this idea to enrich his influential interventionist theory of causal explanation. Here we propose a way to measure causal specificity using tools from information theory. We show that the specificity of a causal variable is not well-defined without a probability distribution over the states of that variable. We demonstrate the tractability and interest of our proposed measure by measuring the (...) specificity of coding DNA and other factors in a simple model of the production of mRNA. (shrink)

In this article I explore the usefulness of Spinoza’s ethics for feminism by considering ways in which it allows feminists to rethink privacy. I draw upon some of Spinoza’s central ideas to address the following question: when should information be classed as private and when should it be communicated? This is a question that is considered by the common law courts. Attempts to find a moral underpinning for such a tortious action against invasions of privacy have tended to draw upon (...) Kant’s categorical imperative. In contrast, I want to consider how Spinoza provides an immanent ethics that reconfigures how privacy is understood. (shrink)

The status of genes as bearers of semantic content remains very much in dispute among philosophers of biology. In a series of papers, Nicholas Shea has argued that his ‘infotel’ theory of semantics vindicates the claim that genes carry semantic content. On Shea’s account, each organism is associated with a ‘developmental system’ that takes genetic representations as inputs and produces whole-organism traits as outputs. Moreover, at least in his most recent work on the topic, Shea is explicit in claiming that (...) these genetic representations are ‘read in ontogenetic time, in the course of individual development’. Here I argue that a close examination of the process of reading, in Shea’s sense, reveals that acts of reading do not actually occur over the course of developmental time at all. To make this vivid, I contrast the process of reading for Shea with another type of developmental process that is widely seen as a form of reading directed on inherited genes, and which certainly does occur over the course of developmental time, namely, gene expression. I suggest that this error in Shea’s thinking can be traced back to an equivocation on Shea’s part in the meaning of ‘reads’, and also to a reliance on an invalid principle regarding the transference of representational content from one token gene to another. The issues at play are bound up with questions about causation and in particular about causation over time. Thus, having first presented my arguments in a way that doesn’t depend on any particular theory of causation, I then make use of Kenneth Waters’ framework of difference-making causation to conceptually sharpen and shed further light on matters. I conclude by discussing a consequence of the fact that acts of reading do not occur in development. 1 Introduction2 Reading for Shea3 Gene Expression as Reading4 Are Genetic Representations Read in Development? Part 15 The Manipulability Theory of Causation and Difference-Making Causation6 Are Genetic Representations Read in Development? Part 27 Conclusion. (shrink)

Natural information refers to the information carried by natural signs such as that smoke is thought to carry natural information about fire. A number of influential philosophers have argued that natural information can also be utilized in a theory of mental content. The most widely discussed account of natural information holds that it results from an extremely strong relation between sign and signified. Critics have responded that it is doubtful that there are many strong relations of this sort in the (...) natural world due to variability between signs and signified. In light of this observation, a promising suggestion is that much of the interesting natural information carried by natural signs is really information with a probabilistic content. However, Dretske’s theory cannot account for this information because it would require implausible second order objective probabilities. Given the most plausible understanding of the probabilities involved here, I argue that it is only sequences of traditional natural signs that carry this probabilistic information. Several implications of this idea will be explored. (shrink)

At the center of Gauker's book stands two inter-connected theses: First, that concepts are dependent on language; second, that this requires rejecting the traditional idea that linguistic communication involves a transmission of thoughts. I argue that we cannot afford to reject the traditional conception of communication and that Gauker's alternative ‘cooperative' conception is unsatisfactory. However, I also argue that Gauker is wrong to suggest that the language dependency thesis of concepts is incompatible with the traditional view of communication.

This essay employs Charles Peirce’s triadic semiotics in order to develop a biosemiotic theory of life that is capable of illuminating the function of information in living systems. Specifically, I argue that the relationship between biological information structures , selecting environments, and the adapted bodily processes of living organisms is aptly modelled by the irreducibly triadic relationship between Peirce’s sign, object, and interpretant, respectively. In each instance of information-based semiosis, the information structure is a complex informational sign that represents the (...) informational object ; and the bodily, behavioral, mental, or intellectual processes that are organized by the informational sign to more or less accurately interpret the present environment constitute a complex informational interpretant—a living, interpreting organism. The essay begins by discussing the precise sense in which this biosemiotic theory is based upon Charles Peirce’s semiotic theory. Next, the theory is developed at length in relation to genetic information structures. Finally, I present a brief outline of how the theory applies to neural and linguistic information structures. The essay concludes with a reflection upon the anti-reductionist implications of the theory. (shrink)

Two-Spirit men's sexual conquest stories—or what I am calling sexual coup stories—narrated more than just the sexual encounter. In fact, actual sexual acts are often secondary to the circumstances producing the sexual encounter. In this study, coup stories serve as a form of data revealing the ways in which sexual conquest is a sociosexual practice thoroughly embedded in broader Native community values and cultural patterns for the movement of bodily desire across landscapes predating humanist intellectual and moral intervention. Thus, the (...) intra-acting agencies of Native sexual circulation provide the opportunity to enact a culturally specific form of material-discursive order that when viewed from the epistemological metropole look highly entropic . Yet, Native sexual ontology realizes itself in the phenomena of a sexual circulation whose material-discursive practices appear to be disordered from the highly ordered humanistic center. (shrink)

In 2002, Luciano Floridi published a paper called What is the Philosophy of Information?, where he argues for a new paradigm in philosophical research. To what extent should his proposal be accepted? Is the Philosophy of Information actually a new paradigm, in the Kuhninan sense, in Philosophy? Or is it only a new branch of Epistemology? In our discussion we will argue in defense of Floridi’s proposal. We believe that Philosophy of Information has the types of features had by other (...) areas already acknowledge as authentic in Philosophy. By way of an analogical argument we will argue that since Philosophy of Information has its own topics, method and problems it would be counter-intuitive not to accept it as a new philosophical area. To strengthen our position we present and discuss main topics of Philosophy of Information. (shrink)

William Dembski claims to have established a decision process to determine when highly unlikely events observed in the natural world are due to Intelligent Design. This article argues that, as no implementable randomness test is superior to a universal Martin-Löf test, this test should be used to replace Dembski's decision process. Furthermore, Dembski's decision process is flawed, as natural explanations are eliminated before chance. Dembski also introduces a fourth law of thermodynamics, his “law of conservation of information,” to argue that (...) information cannot increase by natural processes. However, this article, using algorithmic information theory, shows that this law is no more than the second law of thermodynamics. The article concludes that any discussions on the possibilities of design interventions in nature should be articulated in terms of the algorithmic information theory approach to randomness and its robust decision process. (shrink)

A systematic theory of naturalism, bridging metaphysics and the science of complexity and emergence.

The transition from analogue to digital photography was not accomplished in a single step. It required a number of feeder technologies which enabled and structured the nature of digital photography. Among those traced in this article, the most important is the genesis of the raster grid, which is now hard-wired into the design of the most widely employed photographic chip, the charge-coupled device (CCD). In tracing this history from origins in half-tone printing, the authors argue that qualities available to analogue (...) photographers are no longer available to digital, and that these changes correspond to historical developments in the wider political and economic world. They conclude, however, that these losses may yet be turned into gains. (shrink)

The background of the article is Marxism's lack of a notion of management. The article suggests that anyone rethinking capitalism should pause for a moment to check on the evidence for such a notion. It seems necessary because today's theory of capitalism can no longer be content with a structural theory of the conflict between capital and labour, but must integrate a poststructural, or operational, theory of how capitalism is sustained on a day-to-day basis by organized projects in networks. The (...) article develops a notion of `management by strata', which is matched to the traditional role of hierarchies, and a notion of `management by ties', which is tuned to the newly discovered role of hierarchies in networks. The method used in the article is a theoretical study based on the sociological theories of social systems and networks. (shrink)

Entangled states whose Wigner functions are non-negative may be viewed as being accounted for by local hidden variables (LHV). Recently, there were studies of Bell’s inequality violation (BIQV) for such states in conjunction with the well known theorem of Bell that precludes BIQV for theories that have LHV underpinning. We extend these studies to teleportation which is also based on entanglement. We investigate if, to what extent, and under what conditions may teleportation be accounted for via LHV theory. Our study (...) allows us to expose the role of various quantum requirements. These are, e.g., the uncertainty relation among non-commuting operators, and the no-cloning theorem which forces the complete elimination of the teleported state at its initial port. (shrink)

Arguments for or against a trend in the evolution of complexity are weakened by the lack of an unambiguous definition of complexity. Such definitions abound for both dynamical systems and biological organisms, but have drawbacks of either a conceptual or a practical nature. Physical complexity, a measure based on automata theory and information theory, is a simple and intuitive measure of the amount of information that an organism stores, in its genome, about the environment in which it evolves. It is (...) argued that physical complexity must increase in molecular evolution of asexual organisms in a single niche if the environment does not change, due to natural selection. It is possible that complexity decreases in co‐evolving systems as well as at high mutation rates, in sexual populations, and in time‐dependent landscapes. However, it is reasoned that these factors usually help, rather than hinder, the evolution of complexity, and that a theory of physical complexity for co‐evolving species will reveal an overall trend towards higher complexity in biological evolution. BioEssays 24:1085–1094, 2002. © 2002 Wiley‐Periodicals, Inc. (shrink)

Though we have access to a wealth of information, the main issue is always how to process the available information. How to make sense of all we observe and know. Just like the English alphabet: we know there are 26 letters but unless we put these letters together in a meaningful way, they convey no information. There are infinitely many ways of putting these letters together. Only a small number of those make sense. Only some of those convey exactly what (...) we wish to convey though the message may be interpreted differently by different individuals. That same issue comes up with information: how can we process the information we have? How can we infer and reason under conditions of incomplete observed information? In his seminal book on the philosophy of information, Floridi (2011a) raises a number of open questions. I discuss here one of these questions. That question is how to process information. To do so, I take the more realistic view that information is always limited, incomplete and possibly noisy. I define types of information, relate it to Floridi’s definitions and discuss a basic formulation for processing information under a unified framework. I relate it to some of the basic concepts discussed in the book. (shrink)

The article focuses on the status of the transmission approach to communication. The approach is derived from Claude Shannon’s and Warren Weaver’s mathematical theory of communication, and is primarily used for the analysis of telecommunications processes. Within the model a metaphorical conceptualisation of communication is adopted, as conveying (transmission) of information (thoughts, emotions) from the mind of a subject A to the mind of a subject B. Despite the great popularity of the transmission approach, it is subjected to multilateral criticism. (...) Alternative approaches were formulated in which the transmission metaphor is exceeded, extended or even overcome (e.g., the constitutive, transactional, or the ritual approaches). This paper discusses such criticism. The doubts are raised primarily by the characteristic reductionism and the postulated exclusivity of the transmission approach. A question ariseswhether all the possible types of communication activities can be represented within the transmission approach as a transfer of information. In this context, the dispute between the supporters of the universalistic and the relativistic attitudes to the transmission metaphor is discussed. The polemic also concerns the psychologism elements which are present in the transmission models. Wittgenstein's criticism of psychologism conducted within the framework of his everyday language philosophy is of particular importance. The philosophy may applied to the problem of interpersonal communication. In conclusion it is assumed that the transmission metaphor is important as a tool for the study of many, but not all the aspects of communication. Its importance also lies in the fact that it is the first scientific approach to communication. The exclusivity claims of the transmission model, however, have several limitations, inter alia, it hinders research on the history of communication practices, although the model itself is embedded in a specific historical context. (shrink)

Information changes as it is passed from person to person, with this process of cultural transmission allowing the minds of individuals to shape the information that they transmit. We present mathematical models of cultural transmission which predict that the amount of information passed from person to person should affect the rate at which that information changes. We tested this prediction using a function-learning task, in which people learn a functional relationship between two variables by observing the values of those variables. (...) We varied the total number of observations and the number of those observations that take unique values. We found an effect of the number of observations, with functions transmitted using fewer observations changing form more quickly. We did not find an effect of the number of unique observations, suggesting that noise in perception or memory may have affected learning. (shrink)

We extend the concept that life is an informational phenomenon, at every level of organisation, from molecules to the global ecological system. According to this thesis: living is information processing, in which memory is maintained by both molecular states and ecological states as well as the more obvious nucleic acid coding; this information processing has one overall function—to perpetuate itself; and the processing method is filtration of, and synthesis of, information at lower levels to appear at higher levels in complex (...) systems . We show how information patterns, are united by the creation of mutual context, generating persistent consequences, to result in ‘functional information’. This constructive process forms arbitrarily large complexes of information, the combined effects of which include the functions of life. Molecules and simple organisms have already been measured in terms of functional information content; we show how quantification may be extended to each level of organisation up to the ecological. In terms of a computer analogy, life is both the data and the program and its biochemical structure is the way the information is embodied. This idea supports the seamless integration of life at all scales with the physical universe. The innovation reported here is essentially to integrate these ideas, basing information on the ‘general definition’ of information, rather than simply the statistics of information, thereby explaining how functional information operates throughout life. (shrink)

1. Introduction 2. Reward-Guided Decision Making 3. Content in the Model 4. How to Deflate a Metarepresentational Reading Proust and Carruthers on metacognitive feelings 5. A Deflationary Treatment of RPEs? 5.1 Dispensing with prediction errors 5.2 What is use of the RPE focused on? 5.3 Alternative explanations—worldly correlates 5.4 Contrast cases 6. Conclusion Appendix: Temporal Difference Learning Algorithms.

Response to commentaries on “The Transmission Sense of Information” Content Type Journal Article Pages 195-200 DOI 10.1007/s10539-011-9257-3 Authors Carl T. Bergstrom, Department of Biology, University of Washington, Seattle, WA 98195-1800, USA Martin Rosvall, Integrated Science Lab, Department of Physics, Umeå University, 901 87 Umeå, Sweden Journal Biology and Philosophy Online ISSN 1572-8404 Print ISSN 0169-3867 Journal Volume Volume 26 Journal Issue Volume 26, Number 2.

In its predominant form, the understanding of the neurosciences, which stand in high public esteem, is a naturalistic one. The critique of this naturalism concerns the technical modelling of brain functions as a syntactic or control loop machine. Adequate solutions to the mind-body problem are not found in this way.

This article provides an overview of recent results on lexicographic, linear, and Bayesian models for paired comparison from a cognitive psychology perspective. Within each class, we distinguish subclasses according to the computational complexity required for parameter setting. We identify the optimal model in each class, where optimality is defined with respect to performance when fitting known data. Although not optimal when fitting data, simple models can be astonishingly accurate when generalizing to new data. A simple heuristic belonging to the class (...) of lexicographic models is Take The Best (Gigerenzer & Goldstein (1996) Psychol. Rev. 102: 684). It is more robust than other lexicographic strategies which use complex procedures to establish a cue hierarchy. In fact, it is robust due to its simplicity, not despite it. Similarly, Take The Best looks up only a fraction of the information that linear and Bayesian models require; yet it achieves performance comparable to that of models which integrate information. Due to its simplicity, frugality, and accuracy, Take The Best is a plausible candidate for a psychological model in the tradition of bounded rationality. We review empirical evidence showing the descriptive validity of fast and frugal heuristics. (shrink)

The general concept of information does not belong in the category of universal and inexorable physical laws but in the category of initial conditions and boundary conditions. Boundary conditions formed by local structures are often called constraints. Informational structures such as symbol vehicles are a special type of constraint. It should be clear that the concepts of initial conditions and constraints in physics make no sense outside the context of the law-based physical dynamics to which they apply. This is also (...) the case for the concept of information. -/- . (shrink)

Abstract: According to the Veridicality Thesis, information requires truth. On this view, smoke carries information about there being a fire only if there is a fire, the proposition that the earth has two moons carries information about the earth having two moons only if the earth has two moons, and so on. We reject this Veridicality Thesis. We argue that the main notions of information used in cognitive science and computer science allow A to have information about the obtaining of (...) p even when p is false. (shrink)

Some physicists seem to believe that quantum information theory requires a new concept of information (Jozsa, 1998, Quantum information and its properties. In: Hoi-Kwong Lo, S. Popescu, T. Spiller (Eds.), Introduction to Quantum Computation and Information, World Scientific, Singapore, (pp. 49-75); Deutsch & Hayden, 1999, Information flow in entangled quantum subsystems, preprint quant-ph/9906007). I will argue that no new concept is necessary. Shannon's concept of information is sufficient for quantum information theory. Properties that are cited to contrast quantum information and (...) classical information (i.e., Shannon information) actually point to differences in our ability to manipulate, access, and transfer information depending on whether quantum systems, opposed to classical systems, are used in a communication system. I also demonstrate that conceptually puzzling phenomena in quantum information theory, such as dense coding, teleportation, and Schumacher coding, all of which are cited as evidence that a new concept of information is required, do not have to be regarded as such. (shrink)