What counts as a computation and how it relates to cognitive function are important questions for scientists interested in understanding how the mind thinks. This paper argues that pragmatic aspects of explanation ultimately determine how we answer those questions by examining what is needed to make rigorous the notion of computation used in the (cognitive) sciences. It (1) outlines the connection between the Church-Turing Thesis and computational theories of physical systems, (2) differentiates merely satisfying a computational function from true computation, (...) and finally (3) relates how we determine a true computation to the functional methodology in cognitive science. All of the discussion will be directed toward showing that the only way to connect formal notions of computation to empirical theory will be in virtue of the pragmatic aspects of explanation. (shrink)

Visual Associative agnosia is a rare perceptual impairment generally resulting from lesions in the infero temporal cortex. Patients suffering from associative agnosia are able to make accurate copies of line drawings, but they are unable to visually recognize objects - including those represented in line drawings - as belonging to familiar high-level kinds. The Rich Content View claims that visual experience can represent high-level kind properties. The phenomenon of associative agnosia appears to present us with a strong case for the (...) Rich Content View. There are reasons for thinking that the experiences of an agnosic patient differ from those of a healthy subject. Given that there is a phenomenal contrast between the experiences of an associative agnosic and those of a healthy perceiver, one may argue that this contrast is due to differences in abilities to represent high-level kinds. I claim that there is indeed a phenomenal contrast between the visual experiences of an agnosic and those of a healthy perceiver. However, the explanation of this contrast that best fits the empirical data is compatible with the view that visual experience does not represent high-level kinds. (shrink)

In this article, we argue for the general importance of normative theories of argument strength. We also provide some evidence based on our recent work on the fallacies as to why Bayesian probability might, in fact, be able to supply such an account. In the remainder of the article we discuss the general characteristics that make a specifically Bayesian approach desirable, and critically evaluate putative flaws of Bayesian probability that have been raised in the argumentation literature.

Representations seem to play a major role in many neuroscientific explanations. Philosophers have long attempted to properly define what it means for a neural state to be a representation of a specific content. Teleosemantic theories of content which characterize representations, in part, by appealing to a historical notion of function, are often regarded as our best path towards an account of neural representations. This paper points to the anti-representationalist consequences of these accounts. I argue that assuming such teleosemantic views will (...) deprive representations of their explanatory role in computational explanations. My argument rests on the claim that many explanations in cognitive neuroscience are entirely independent of any historical considerations. In making this claim, I will also offer an adapted version of the famous Swampperson thought experiment, which is better suited to discussions of subpersonal neural representations. (shrink)

Work on analogy has been done from a number of disciplinary perspectives throughout the history of Western thought. This work is a multidisciplinary guide to theorizing about analogy. It contains 1,406 references, primarily to journal articles and monographs, and primarily to English language material. classical through to contemporary sources are included. The work is classified into eight different sections (with a number of subsections). A brief introduction to each section is provided. Keywords and key expressions of importance to research on (...) analogy are discussed in the introductory material. Electronic resources for conducting research on analogy are listed as well. (shrink)

The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in (...) parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language. Key Words: efference copies; emulation theory of representation; forward models; Kalman filters; motor control; motor imagery; perception; visual imagery. (shrink)

Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the (...) notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call “resource-rational analysis.”. (shrink)

Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that language themselves. We analyze the consequences of iterated learning for learning algorithms based on the principles of Bayesian inference, assuming that learners compute a posterior distribution over languages by combining a prior (representing their inductive biases) with the evidence provided by linguistic data. We show that when learners sample languages from this posterior (...) distribution, iterated learning converges to a distribution over languages that is determined entirely by the prior. Under these conditions, iterated learning is a form of Gibbs sampling, a widely-used Markov chain Monte Carlo algorithm. The consequences of iterated learning are more complicated when learners choose the language with maximum posterior probability, being affected by both the prior of the learners and the amount of information transmitted between generations. We show that in this case, iterated learning corresponds to another statistical inference algorithm, a variant of the expectation-maximization (EM) algorithm. These results clarify the role of iterated learning in explanations of linguistic universals and provide a formal connection between constraints on language acquisition and the languages that come to be spoken, suggesting that information transmitted via iterated learning will ultimately come to mirror the minds of the learners. (shrink)

A semantics of pictorial representation should provide an account of how pictorial signs are associated with the contents they express. Unlike the familiar semantics of spoken languages, this problem has a distinctively spatial cast for depiction. Pictures themselves are two-dimensional artifacts, and their contents take the form of pictorial spaces, perspectival arrangements of objects and properties in three dimensions. A basic challenge is to explain how pictures are associated with the particular pictorial spaces they express. Inspiration here comes from recent (...) proposals that analyze depiction in terms of geometrical projection. In this essay, I will argue that, for a central class of pictures, the projection-based theory of depiction provides the best explanation for how pictures express pictorial spaces, while rival perceptual and resemblance theories fall short. Since the composition of pictorial space is itself the basis for all other aspects of pictorial content, the proposal provides a natural foundation for further pictorial semantics. (shrink)

What is the best account of process reliabilism about epistemic justification, especially epistemic entitlement? I argue that entitlement consists in the normal functioning (proper operation) of the belief-forming process when the process has forming true beliefs reliably as an etiological function. Etiological functions involve consequence explanation: a belief-forming process has forming true beliefs reliably as a function just in case forming-true beliefs reliably partly explains the persistence of the process. This account paves the way for avoiding standard objections to process (...) reliabilism and situations epistemic entitlement within a normative framework of functions and functional norms. (shrink)

Fodor claims that cognitive modules can be thought of as constituting a psychological natural kind in virtue of their possession of most or all of nine specified properties. The challenge to this considered here comes from synaesthesia. Synaesthesia is a type of cross-modal association: input to one sensory modality reliably generates an additional sensory output that is usually generated by the input to a distinct sensory modality. The most common form of synaesthesia manifests Fodor's nine specified properties of modularity, and (...) hence, according to Segal (1997), it should be understood as involving an extra module. Many psychologists believe that synaesthesia involves a breakdown in modularity. After outlining how both theories can explain the manifestation of the nine alleged properties of modularity in synaesthesia, I discuss the two concepts of function which initially motivate the respective theories. I argue that only a teleological concept of function is properly able to adjudicate between the two theories. The upshot is a further application of so-called externalist considerations to mental phenomena. (shrink)

Vision is so closely identified with visual phenomenology that we sometimes forget that the visual system does more than deliver our experience of the world. Vision also plays a critical role in the control of our movements, from picking up our coffee cups to playing tennis. But the visual control of movement has, until recently, been relatively neglected. Indeed, traditional accounts of vision, while acknowledging the role of vision in motor control, have simply regarded such control as part of a (...) larger function – that of constructing an internal model of the external world. Even though such accounts might postulate separate ‘modules’ for the processing of different visual features, such as motion, colour, texture, and form, in most of these accounts there is an implicit assumption that, in the end, vision delivers a single representation of the external world – a kind of simulacrum of the real thing that serves as the perceptual foundation for all visually driven thought and action. (shrink)

Two major functions of the visual system are discussed and contrasted. One function of vision is the creation of an internal model or percept of the external world. Most research in object perception has concentrated on this aspect of vision. Vision also guides the control of object-directed action. In the latter case, vision directs our actions with respect to the world by transforming visual inputs into appropriate motor outputs. We argue that separate, but interactive, visual systems have evolved for the (...) perception of objects on the one hand and the control of actions directed at those objects on the other. This 'duplex' approach to high-level vision suggests that Marrian or 'reconstructive' approaches and Gibsonian or 'purposive-animate-behaviorist' approaches need not be seen as mutually exclusive, but rather as complementary in their emphases on different aspects of visual function. (shrink)

The resurgence of interest in collective behavior is in large part due to tools recently made available for conducting laboratory experiments on groups, statistical methods for analyzing large data sets reflecting social interactions, the rapid growth of a diverse variety of online self‐organized collectives, and computational modeling methods for understanding both universal and scenario‐specific social patterns. We consider case studies of collective behavior along four attributes: the primary motivation of individuals within the group, kinds of interactions among individuals, typical dynamics (...) that result from these interactions, and characteristic outcomes at the group level. With this framework, we compare the collective patterns of noninteracting decision makers, bee swarms, groups forming paths in physical and abstract spaces, sports teams, cooperation and competition for resource usage, and the spread and extension of innovations in an online community. Some critical issues surrounding collective behavior are then reviewed, including the questions of “Does group behavior always reduce to individual behavior?”“Is ‘group cognition’ possible?” and “What is the value of formal modeling for understanding group behavior?”. (shrink)

Molyneux’s question, whether the newly sighted might immediately recognize tactilely familiar shapes by sight alone, has produced an array of answers over three centuries of debate and discussion. I propose the first pluralist response: many different answers, both yes and no, are individually sufficient as an answer to the question as a whole. I argue that this is possible if we take the question to be cluster concept of sub-problems. This response opposes traditional answers that isolate specific perceptual features as (...) uniquely applicable to Molyneux’s question and grant viability to only one reply. Answering Molyneux’s question as a cluster concept may also serve as a methodology for resolving other philosophical problems. (shrink)

The claim that the disorganized subtype of schizophrenia results from glutamate hypofunction is enhanced by consideration of current subtypology of schizophrenia, symptom definition, interdependence of neurotransmitters, and the nature of the data needed to support the hypothesis. Careful specification clarifies the clinical reality of disorganization as a feature of schizophrenia and increases the utility of the subtype.

The various behavioral disciplines model human behavior in distinct and incompatible ways. Yet, recent theoretical and empirical developments have created the conditions for rendering coherent the areas of overlap of the various behavioral disciplines. The analytical tools deployed in this task incorporate core principles from several behavioral disciplines. The proposed framework recognizes evolutionary theory, covering both genetic and cultural evolution, as the integrating principle of behavioral science. Moreover, if decision theory and game theory are broadened to encompass other-regarding preferences, they (...) become capable of modeling all aspects of decision making, including those normally considered “psychological,” “sociological,” or “anthropological.” The mind as a decision-making organ then becomes the organizing principle of psychology. (Published Online April 27 2007) Key Words: behavioral game theory; behavioral science; evolutionary theory; experimental psychology; gene-culture coevolution; rational actor model; socialization. (shrink)

This paper presents an attempt to bridge the gap between logical and cognitive treatments of strategic reasoning in games. There have been extensive formal debates about the merits of the principle of backward induction among game theorists and logicians. Experimental economists and psychologists have shown that human subjects, perhaps due to their bounded resources, do not always follow the backward induction strategy, leading to unexpected outcomes. Recently, based on an eye-tracking study, it has turned out that even human subjects who (...) produce the outwardly correct ‘backward induction answer’ use a different internal reasoning strategy to achieve it. The paper presents a formal language to represent different strategies on a finer-grained level than was possible before. The language and its semantics help to precisely distinguish different cognitive reasoning strategies, that can then be tested on the basis of computational cognitive models and experiments with human subjects. The syntactic framework of the formal system provides a generic way of constructing computational cognitive models of the participants of the Marble Drop game. (shrink)

How do people reason about their opponent in turn-taking games? Often, people do not make the decisions that game theory would prescribe. We present a logic that can play a key role in understanding how people make their decisions, by delineating all plausible reasoning strategies in a systematic manner. This in turn makes it possible to construct a corresponding set of computational models in a cognitive architecture. These models can be run and fitted to the participants’ data in terms of (...) decisions, response times, and answers to questions. We validate these claims on the basis of an earlier game-theoretic experiment about the turn-taking game “Marble Drop with Surprising Opponent”, in which the opponent often starts with a seemingly irrational move. We explore two ways of segregating the participants into reasonable “player types”. The first way is based on latent class analysis, which divides the players into three classes according to their first decisions in the game: Random players, Learners, and Expected players, who make decisions consistent with forward induction. The second way is based on participants’ answers to a question about their opponent, classified according to levels of theory of mind: zero-order, first-order and second-order. It turns out that increasing levels of decisions and theory of mind both correspond to increasing success as measured by monetary awards and increasing decision times. Next, we use the logical language to express different kinds of strategies that people apply when reasoning about their opponent and making decisions in turn-taking games, as well as the ‘reasoning types’ reflected in their behavior. Then, we translate the logical formulas into computational cognitive models in the PRIMs architecture. Finally, we run two of the resulting models, corresponding to the strategy of only being interested in one’s own payoff and to the myopic strategy, in which one can only look ahead to a limited number of nodes. It turns out that the participant data fit to the own-payoff strategy, not the myopic one. The article closes the circle from experiments via logic and cognitive modelling back to predictions about new experiments. (shrink)

In reinforcement learning, a decision maker searching for the most rewarding option is often faced with the question: What is the value of an option that has never been tried before? One way to frame this question is as an inductive problem: How can I generalize my previous experience with one set of options to a novel option? We show how hierarchical Bayesian inference can be used to solve this problem, and we describe an equivalence between the Bayesian model and (...) temporal difference learning algorithms that have been proposed as models of RL in humans and animals. According to our view, the search for the best option is guided by abstract knowledge about the relationships between different options in an environment, resulting in greater search efficiency compared to traditional RL algorithms previously applied to human cognition. In two behavioral experiments, we test several predictions of our model, providing evidence that humans learn and exploit structured inductive knowledge to make predictions about novel options. In light of this model, we suggest a new interpretation of dopaminergic responses to novelty. (shrink)

Critical notice of Andy Clark's "Associative Engines".

This target article draws together two groups of experimental studies on the control of human movement through peripheral feedback and centrally generated signals of motor commands. First, during natural movement, feedback from muscle, joint, and cutaneous afferents changes; in human subjects these changes have reflex and kinesthetic consequences. Recent psychophysical and microneurographic evidence suggests that joint and even cutaneous afferents may have a proprioceptive role. Second, the role of centrally generated motor commands in the control of normal movements and movements (...) following acute and chronic deafferentation is reviewed. There is increasing evidence that subjects can perceive their motor commands under various conditions, but that this is inadequate for normal movement; deficits in motor performance arise when the reliance on proprioceptive feedback is abolished either experimentally or because of pathology. During natural movement, the CNS appears to have access to functionally useful input from a range of peripheral receptors as well as from internally generated command signals. The unanswered questions that remain suggest a number of avenues for further research. (shrink)

A central question, if not the central question, of philosophy of perception is whether sensory states have a nature similar to thoughts about the world, whether they are essentially representational. According to the content view, at least some of our sensory states are, at their core, representations with contents that are either accurate or inaccurate. Tyler Burge’s Origins of Objectivity is the most sustained and sophisticated defense of the content view to date. His defense of the view is problematic in (...) several ways. The most significant problem is that his approach does not sit well with mainstream perceptual psychology. (shrink)

Like the information patterns that evolve through. biological processes, mental representations or memes evolve through adaptive exploration and transformation of an information space through variation, selection, and transmission. However since memes do not contain instructions for their replication our brains do it for them, strategically, guided by a fitness landscape that reflects both internal drives and a worldview that forms through meme assimilation. This paper presents a tentative model for how an individual becomes a meme evolving agent via the emergence (...) of an autocatalytic network of sparse, distributed memories, and discusses implications for complex creative thought processes and why they are unique to humans. A hypothetical scenario for the evolutionary dynamics of a given meme in a society of interacting individuals is presented. (shrink)

Do accounts of scientific theory formation and revision have implications for theories of everyday cognition? We maintain that failing to distinguish between importantly different types of theories of scientific inference has led to fundamental misunderstandings of the relationship between science and everyday cognition. In this article, we focus on one influential manifestation of this phenomenon which is found in Fodor's well-known critique of theories of cognitive architecture. We argue that in developing his critique, Fodor confounds a variety of distinct claims (...) about the holistic nature of scientific inference. Having done so, we outline more promising relations that hold between theories of scientific inference and ordinary cognition. (shrink)

In this paper I argue that a principal argument in favor of the existence of non-conceptual content (henceforth NCC) fails. That is, I do not accept that considerations regarding the richness of our perceptual experiences support the existence of NCC. I argue instead that the existence of NCC is empirically motivated. Here is an outline of the paper. First, I set out the distinction between conceptual content and NCC as we understand it. Second, I consider the richness argument (RA), and (...) argue that it fails. I argue in particular that RA (or RA-style arguments) are either self-defeating or confl ict with reasonably established accounts of early perceptual processing. Third, I tackle a residual phenomenological puzzle and offer a solution to it. Fourth, I argue that the existence of NCC enjoys empirical support. I argue in particular that states associated with early stages of visual perceptual processing have NCC. (shrink)

In the study of cognitive processes, limitations on computational resources (computing time and memory space) are usually considered to be beyond the scope of a theory of competence, and to be exclusively relevant to the study of performance. Starting from considerations derived from the theory of computational complexity, in this paper I argue that there are good reasons for claiming that some aspects of resource limitations pertain to the domain of a theory of competence.

This book is an excellent manifesto for future work in child development. It presents a multidisciplinary approach that clearly demonstrates the value of integrating modeling, neuroscience, and behavior to explore the mechanisms underlying development and to show how internal context-dependent representations arise and are modified during development. Its only major flaw is to have given short shrift to the study of the role of genetics on development.

The entropy-reduction hypothesis claims that the cognitive processing difficulty on a word in sentence context is determined by the word's effect on the uncertainty about the sentence. Here, this hypothesis is tested more thoroughly than has been done before, using a recurrent neural network for estimating entropy and self-paced reading for obtaining measures of cognitive processing load. Results show a positive relation between reading time on a word and the reduction in entropy due to processing that word, supporting the entropy-reduction (...) hypothesis. Although this effect is independent from the effect of word surprisal, we find no evidence that these two measures correspond to cognitively distinct processes. (shrink)

Evolutionary psychology is widely understood as involving an integration of evolutionary theory and cognitive psychology, in which the former promises to revolutionise the latter. In this paper, I suggest some reasons to doubt that the assumptions of evolutionary theory and of cognitive psychology are as directly compatible as is widely assumed. These reasons relate to three different problems of specifying adaptive functions as the basis for characterising cognitive mechanisms: the disjunction problem, the grain problem and the environment problem. Each of (...) these problems can be understood as arising from incommensurate characterisations of the nature and role of 'the environment' in the two approaches. Purported solutions to the problems appear to require detailed information concerning the EEA (environment of evolutionary adaptedness), with the disjunction problem placing the lowest requirement, the environment problem placing the highest requirement, and the grain problem placing an intermediate one. In each case, such information is not likely to be forthcoming, because it may require iterating through successively more distant EEA's with no principled stopping point. This produces a dilemma for evolutionary psychology - either to solve these apparently insoluble problems, or to attempt to avoid them but in doing so forego detailed evolutionary constraints on cognition. (shrink)

This article presents a detailed formal approach to concepts and concept combination. Sense generation is a competence‐level theory that attempts to respect constraints from the various cognitive sciences, and postulates “quasi‐classical” conceptual structures where attributes receive only one value (but are defeasible and so do not represent necessary and sufficient conditions on category membership) and where classification is binary (but explicitly context‐sensitive). It is also argued that any general theory of concepts must account for “privative” combinations (e.g., stone lion, fake (...) gun, apparent friend) as extreme test‐cases of representational and classificatory flexibility. The approach presented therefore provides a treatment of these combinations. The approach differentiates between the “lexical concept” (the stable information represented in a mental lexicon) which acts as a base from which the various “senses” (flexible contents associated with words and phrases in context, and used in classification) are “generated.” Generation allows nonmonotonicity, so that in different circumstances, different attributes may be defeated or modified. Classification is treated as relative to the perspective adopted, so that a classification acceptable from one perspective may be unacceptable from another, without contradiction. The result is a view that assumes bottom‐up priority in concept combination, where the range of senses generated by bottom‐up rules of combination is tempered by pragmatic‐communicative constraints on classification. An account of the representational and classification behavior of privative combinations is outlined, and the article concludes with a discussion of some of the implications of the approach. (shrink)

According to one brand of 'externalism', cognitive theories should individuate mental content 'widely'--that is, partly in terms of environmental features. David Marr's theory of vision is often cited in support of this view. Many philosophers (most notably, Tyler Burge) regard it as a prime example of a fruitful cognitive theory that widely individuates the representations it posits. I argue that, contrary to popular belief, Marr's theory does not presuppose an externalist view of mental content.

One of the central issues in cognitive science is the nature of human representations. We argue that symbolic representations are essential for capturing human cognitive capabilities. We start by examining some common misconceptions found in discussions of representations and models. Next we examine evidence that symbolic representations are essential for capturing human cognitive capabilities, drawing on the analogy literature. Then we examine fundamental limitations of feature vectors and other distributed representations that, despite their recent successes on various practical problems, suggest (...) that they are insufficient to capture many aspects of human cognition. After that, we describe the implications for cognitive architecture of our view that analogy is central, and we speculate on roles for hybrid approaches. We close with an analogy that might help bridge the gap. (shrink)

The theory of fast and frugal heuristics, developed in a new book called Simple Heuristics that make Us Smart (Gigerenzer, Todd, and the ABC Research Group, in press), includes two requirements for rational decision making. One is that decision rules are bounded in their rationality –- that rules are frugal in what they take into account, and therefore fast in their operation. The second is that the rules are ecologically adapted to the environment, which means that they `fit to reality.' (...) The main purpose of this article is to apply these ideas to learning rules–-methods for constructing, selecting, or evaluating competing hypotheses in science, and to the methodology of machine learning, of which connectionist learning is a special case. The bad news is that ecological validity is particularly difficult to implement and difficult to understand. The good news is that it builds an important bridge from normative psychology and machine learning to recent work in the philosophy of science, which considers predictive accuracy to be a primary goal of science. (shrink)

Analogy and similarity are central phenomena in human cognition, involved in processes ranging from visual perception to conceptual change. To capture this centrality requires that a model of comparison must be able to integrate with other processes and handle the size and complexity of the representations required by the tasks being modeled. This paper describes extensions to Structure-Mapping Engine since its inception in 1986 that have increased its scope of operation. We first review the basic SME algorithm, describe psychological evidence (...) for SME as a process model, and summarize its role in simulating similarity-based retrieval and generalization. Then we describe five techniques now incorporated into the SME that have enabled it to tackle large-scale modeling tasks: Greedy merging rapidly constructs one or more best interpretations of a match in polynomial time: O); Incremental operation enables mappings to be extended as new information is retrieved or derived about the base or target, to model situations where information in a task is updated over time; Ubiquitous predicates model the varying degrees to which items may suggest alignment; Structural evaluation of analogical inferences models aspects of plausibility judgments; Match filters enable large-scale task models to communicate constraints to SME to influence the mapping process. We illustrate via examples from published studies how these enable it to capture a broader range of psychological phenomena than before. (shrink)

A leading theoretical framework for naturalistic explanation of mind holds that we explain the mind by positing progressively "stupider" capacities ("homunculi") until the mind is "discharged" by means of capacities that are not intelligent at all. The so-called homuncular fallacy involves violating this procedure by positing the same capacities at subpersonal levels. I argue that the homuncular fallacy is not a fallacy, and that modern-day homunculi are idle posits. I propose an alternative view of what naturalism requires that reflects how (...) the cognitive sciences are actually integrating mind and matter. (shrink)

I review a widely accepted argument to the conclusion that the contents of our beliefs, desires and other mental states cannot be causally efficacious in a classical computational model of the mind. I reply that this argument rests essentially on an assumption about the nature of neural structure that we have no good scientific reason to accept. I conclude that computationalism is compatible with wide semantic causal efficacy, and suggest how the computational model might be modified to accommodate this possibility.

The Ollivier–Poulin–Zurek definition of objectivity provides a philosophical basis for the environment as witness formulation of decoherence theory and hence for quantum Darwinism. It is shown that no account of the reference of the key terms in this definition can be given that does not render the definition inapplicable within quantum theory. It is argued that this is not the fault of the language used, but of the assumption that the laws of physics are independent of Hilbert-space decomposition. All evidence (...) suggests that this latter assumption is true. If it is, decoherence cannot explain the emergence of classicality. (shrink)