The paper attempts to analyze in some detail the main problems encountered in reasoning using diagrams, which may cause errors in reasoning, produce doubts concerning the reliability of diagrams, and impressions that diagrammatic reasoning lacks the rigour necessary for mathematical reasoning. The paper first argues that such impressions come from long neglect which led to a lack of well-developed, properly tested and reliable reasoning methods, as contrasted with the amount of work generations of mathematicians expended on refining the methods of (...) reasoning with formulae and predicate calculus. Next, two main groups of problems occurring in diagrammatic reasoning are introduced. The second group, called diagram imprecision, is then briefly summarized, its detailed analysis being postponed to another paper. The first group, called collectively the generalization problem, is analyzed in detail in the rest of the paper. The nature and causes of the problems from this group are explained, methods of detecting the potentially harmful occurrences of these problems are discussed, and remedies for possible errors they may cause are proposed. Some of the methods are adapted from similar methods used in reasoning with formulae, several other problems constitute new, specifically diagrammatic ways of reliable reasoning. (shrink)
A new book by Zenon Pylyshyn is always a cause for celebration among philosophers of psychology. While many hard-nosed experimental cognitive scientists are attentive to philosophers’ concerns, Pylyshyn stands alone in the extraordinary efforts he takes to understand, address, and struggle with the philosophical puzzles that the mind, and perception in particular, raises. Pylyshyn’s most recent work, Things and Places: How the Mind Connects with the World, does not disappoint. It is philosophically rich. Indeed, the approach to object perception (...) that Pylyshyn develops in this book takes inspiration from Evans’s (1982) and Perry’s (1979) work on demonstratives and indexicals, draws on Dretskean (1981, 1986, 1988) ideas about representation, and tangles with Strawson (1959), Quine (1992), and Clark (2000, 2004) over how to understand the role of concepts in perception. In short, it is just the kind of book philosophers of psychology should lavishly slather with clotted cream and joyously devour at their next tea party. The main focus of this review will be Pylyshyn’s theory of FINSTs (an acronym for Fingers of INSTantion, for reasons to be soon clarified). FINSTs are the primary subject of the first three chapters of Things and Places, after which they basically disappear for about eighty pages, to reappear in the final and lengthiest fifth chapter, where they are put to use in a speculative (and, to my mind, slightly incredible) explanation of data from mental imagery experiments. The fourth chapter is an engaging polemic against using subjective experience as a source of evidence about psychological processing and, in particular, the danger in assuming that because mental images appear to have spatial properties, they must be represented spatially. This chapter stands alone and would be of interest to followers of the imagery debate or, for that matter, to instructors looking for counter-examples when.. (shrink)
The imagery debate re-enacts controversies persisting since Descartes. The controversy remains important less for what we can learn about visual imagery than about cognitive science itself. In the tradition of Arnauld, Reid, Bartlett, Austin and Ryle, Pylyshyn’s critique exposes notorious mistakes being unwittingly rehearsed not only regarding imagery but also in several independent domains of research in modern cognitive science.
This paper tries to clarify the double reading of time found in the surviving sources of the Stoic School, making use of the parallelism between time and the other incorporeals (the couple void-place and the so-called sayable). Secondly, it aims to extend the research to Ethics, a discipline that acts as the summit to the system and from which it is possible to grasp the key role that Time plays in Stoicism as a whole and in its bitter reaction against (...) Aristotelism. (shrink)
Zenons Politeia, der Entwurf eines idealen Staates aus G ttern und Weisen, erf hrt in der vorliegenden Studie eine neue Deutung als Gesellschaftsform, in der das Leben nach dem Gesetz der Natur verwirklicht ist.
This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...) e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)
Although the study of visual perception has made more progress in the past 40 years than any other area of cognitive science, there remain major disagreements as to how closely vision is tied to general cognition. This paper sets out some of the arguments for both sides (arguments from computer vision, neuroscience, Psychophysics, perceptual learning and other areas of vision science) and defends the position that an important part of visual perception, which may be called early vision or just vision, (...) is prohibited from accessing relevant expectations, knowledge and utilities - in other words it is cognitively impenetrable. That part of vision is complex and articulated and provides a representation of the 3-D surfaces of objects sufficient to serve as an index into memory, with somewhat different outputs being made available to other systems such as those dealing with motor control. The paper also addresses certain conceptual and methodological issues, including the use of signal detection theory and event-related potentials to assess cognitive penetration of vision. A distinction is made among several stages in visual processing. These include, in addition to the inflexible early-vision stage, a pre-perceptual attention allocation stage and a post-perceptual evaluation, memory-accessing, and inference stage which provide several different highly constrained ways in which cognition can affect the outcome of visual perception. The paper discusses arguments that have been presented in both computer vision and psychology showing that vision is "intelligent" and involves elements of problem solving". It is suggested that these cases do not show cognitive penetration, but rather they show that certain natural constraints on interpretation, concerned primarily with optical and geometrical properties of the world, have been compiled into the visual system. The paper also examines a number of examples where instructions and "hints" are alleged to affect. (shrink)
It is generally accepted that there is something special about reasoning by using mental images. The question of how it is special, however, has never been satisfactorily spelled out, despite more than thirty years of research in the post-behaviorist tradition. This article considers some of the general motivation for the assumption that entertaining mental images involves inspecting a picture-like object. It sets out a distinction between phenomena attributable to the nature of mind to what is called the cognitive architecture, and (...) ones that are attributable to tacit knowledge used to simulate what would happen in a visual situation. With this distinction in mind, the paper then considers in detail the widely held assumption that in some important sense images are spatially displayed or are depictive, and that examining images uses the same mechanisms that are deployed in visual perception. I argue that the assumption of the spatial or depictive nature of images is only explanatory if taken literally, as a claim about how images are physically instantiated in the brain, and that the literal view fails for a number of empirical reasons – for example, because of the cognitive penetrability of the phenomena cited in its favor. Similarly, while it is arguably the case that imagery and vision involve some of the same mechanisms, this tells us very little about the nature of mental imagery and does not support claims about the pictorial nature of mental images. Finally, I consider whether recent neuroscience evidence clarifies the debate over the nature of mental images. I claim that when such questions as whether images are depictive or spatial are formulated more clearly, the evidence does not provide support for the picture-theory over a symbol-structure theory of mental imagery. Even if all the empirical claims were true, they do not warrant the conclusion that many people have drawn from them: that mental images are depictive or are displayed in some (possibly cortical) space. Such a conclusion is incompatible with what is known about how images function in thought. We are then left with the provisional counterintuitive conclusion that the available evidence does not support rejection of what I call the “null hypothesis”; namely, that reasoning with mental images involves the same form of representation and the same processes as that of reasoning in general, except that the content or subject matter of thoughts experienced as images includes information about how things would look. (shrink)
When in 1979 Zenon Pylyshyn, associate editor of Behavioral and Brain Sciences (BBS, a peer commentary journal which I edit) informed me that he had secured a paper by John Searle with the unprepossessing title of [XXXX], I cannot say that I was especially impressed; nor did a quick reading of the brief manuscript -- which seemed to be yet another tedious "Granny Objection" about why/how we are not computers -- do anything to upgrade that impression.
I set out two theses. The first is Lynn Robertson’s: (a) spatial awareness is a cause of object perception. A natural counterpoint is: (b) spatial awareness is a cause of your ability to make accurate verbal reports about a perceived object. Zenon Pylyshyn has criticized both. I argue that nonetheless, the burden of the evidence supports both (a) and (b). Finally, I argue conscious visual perception of an object has a different causal role to both: (i) non-conscious perception of (...) the object, and (ii) experience, e.g. hallucination, that may be subjectively indiscriminable from, but is not, perception of the object. (shrink)
People have always wondered how thinking takes place and what thoughts are constructed from. We typically experience our thoughts as involving pictorial (or sensory) contents or as being in words. Although this idea has been enshrined in psychology as the “dual code” theory of reasoning and memory, serious questions have been raised concerning this view. It appears that whatever the form of our thoughts it is unlikely that it is anything like our experience of them. But if thought is not (...) in pictures or words, what form does it take? If we do not sometimes think in words, then what actually goes on when we think by engaging in an “inner dialogue”? And if we do not sometimes think in pictures, what goes on when we reason by creating and examining “mental images”? (shrink)
One of the main challenges that Jerry Fodor and Zenon Pylyshyn (Cognition 28:3–71, 1988) posed for any connectionist theory of cognitive architecture is to explain the systematicity of thought without implementing a Language of Thought (LOT) architecture. The systematicity challenge presents a dilemma: if connectionism cannot explain the systematicity of thought, then it fails to offer an adequate theory of cognitive architecture; and if it explains the systematicity of thought by implementing a LOT architecture, then it fails to offer (...) an alternative to the LOT hypothesis. Given that thought is systematic, connectionism can offer an adequate alternative to the LOT hypothesis only if it can meet the challenge. Although some critics tried to meet the challenge, others argued that it need not be met since thought is not in fact systematic; and some claimed not to even understand the claim that thought is systematic. I do not here examine attempts to answer the challenge. Instead, I defend the challenge itself by explicating the notion of systematicity in a way that I hope makes clear that thought is indeed systematic, and so that to offer an adequate alternative to the LOT hypothesis, connectionism must meet the challenge. (shrink)
the _algorithmic_, and the _implementational_; Zenon Pylyshyn (1984) calls them the _semantic_, the _syntactic_, and the _physical_; and textbooks in cognitive psychology sometimes call them the levels of _content_, _form_, and _medium_ (e.g. Glass, Holyoak, and Santa 1979).
In the past decade there has been renewed interest in the study of mental imagery. Emboldened by new findings from neuroscience, many people have revived the idea that mental imagery involves a special format of thought, one that is pictorial in nature. But the evidence and the arguments that exposed deep conceptual and empirical problems in the picture theory over the past 300 years have not gone away. I argue that the new evidence from neural imaging and clinical neuropsychology does (...) little to justify this recidivism because it does not address the format of mental images. I also discuss some reasons why the picture theory is so resistant to counterarguments and suggest ways in which non-pictorial theories might account for the apparent spatial nature of images. (shrink)
Jacques Mehler was notoriously charitable in embracing a diversity of approaches to science and to the use of many different methodologies. One place where his ecumenism brought the two of us into disagreement is when the evidence of brain imaging was cited in support of different psychological doctrines, such as the picture-theory of mental imagery. Jacques remained steadfast in his faith in the ability of neuroscience data (where the main source of evidence has been from clinical neurology and neuro-imaging) to (...) choose among different psychological positions. I personally have seen little reason for this optimism so Jacques and I frequently found ourselves disagreeing on this issue, though I should add that we rarely disagreed on substantive issues on which we both had views. This particular bone of contention, however, kept us busy at parties and during the many commutes between New York and New Jersey, where Jacques was a frequent visitor at the Rutgers Center for Cognitive Science. Now that I am in a position where he is a captive audience it seems an opportune time to raise the question again. (shrink)
In an influential critique, Jerry Fodor and Zenon Pylyshyn point to the existence of a potentially devastating dilemma for connectionism (Fodor and Pylyshyn ). Either connectionist models consist in mere associations of unstructured representations, or they consist in processes involving complex representations. If the former, connectionism is mere associationism, and will not be capable of accounting for very much of cognition. If the latter, then connectionist models concern only the implementation of cognitive processes, and are, therefore, not informative at (...) the level of cognition. I shall argue that Fodor and Pylyshyn's argument is based on a crucial misunderstanding, the same misunderstanding which motivates the entire language of thought hypothesis. (shrink)
This paper argues that a theory of situated vision, suited for the dual purposes of object recognition and the control of action, will have to provide something more than a system that constructs a conceptual representation from visual stimuli: it will also need to provide a special kind of direct (preconceptual, unmediated) connection between elements of a visual representation and certain elements in the world. Like natural language demonstratives (such as `this' or `that') this direct connection allows entities to be (...) referred to without being categorized or conceptualized. Several reasons are given for why we need such a preconcep- tual mechanism which individuates and keeps track of several individual objects in the world. One is that early vision must pick out and compute the relation among several individual objects while ignoring their properties. Another is that incrementally computing and updating representations of a dynamic scene requires keeping track of token individuals despite changes in their properties or locations. It is then noted that a mechanism meeting these requirements has already been proposed in order to account for a number of disparate empiri- cal phenomena, including subitizing, search-subset selection and multiple object tracking (Pylyshyn et al., Canadian Journal of Experimental Psychology 48(2) (1994) 260). This mechanism, called a visual index or FINST, is brie. (shrink)
This paper contrasts three different schemes of reference relevant to understanding systems of perceptual representation: a location-based system dubbed "feature-placing", a system of "visual indices" referring to things called "proto-objects", and the full sortal-based individuation allowed by a natural language. The first three sections summarize some of the key arguments (in Clark, 2000) to the effect that the early, parallel, and pre-attentive registration of sensory features itself constitutes a simple system of nonconceptual mental representation. In particular, feature integration--perceiving something as (...) being both F and G, where F and G are sensible properties registered in distinct parallel streams--requires a referential apparatus. Section V. reviews some grounds for thinking that at these earliest levels this apparatus is location-based: that it has a direct and nonconceptual means of picking out places. Feature-placing is contrasted with a somewhat more sophisticated system that can identify and track four or five "perceptual objects" or "proto-objects", independently of their location, for as long as they remain perceptible. Such a system is found in Zenon Pylyshyn's fascinating work on "visual indices", in Dana Ballard's notion of deictic codes, and in Kahneman, Treisman, and Wolfe's accounts of systems of evanescent representations they call "object files". Perceptual representation is a layered affair, and I argue that it probably includes both feature-placing and proto-objects. Finally, both nonconceptual systems are contrasted with the full-blooded individuation allowed in a natural language. (shrink)
inﬂuence. One of the principal characteristics that distinguishes Cognitive Science from more traditional studies of cognition within Psychology, is the extent to which it has been inﬂuenced by both the ideas and the techniques of computing. It may come as a surprise to the outsider, then, to discover that there is no unanimity within the discipline on either (a) the nature (and in some cases the desireabilty) of the inﬂuence and (b) what computing is –- or at least on its.
Since the early eighties, computationalism in the study of the mind has been “under attack” by several critics of the so-called “classic” or “symbolic” approaches in AI and cognitive science. Computationalism was generically identified with such approaches. For example, it was identified with both Allen Newell and Herbert Simon’s Physical Symbol System Hypothesis and Jerry Fodor’s theory of Language of Thought, usually without taking into account the fact ,that such approaches are very different as to their methods and aims. (...) class='Hi'>Zenon Pylyshyn, in his influential book Computation and Cognition, claimed that both Newell and Fodor deeply influenced his ideas on cognition as computation. This probably added to the confusion, as many people still consider Pylyshyn’s book as paradigmatic of the computational approach in the study of the mind. Since then, cognitive scientists, AI researchers and also philosophers of the mind have been asked to take sides on different “paradigms” that have from time to time been proposed as opponents of (classic or symbolic) computationalism. Examples of such oppositions are: -/- computationalism vs. connectionism, computationalism vs. dynamical systems, computationalism vs. situated and embodied cognition, computationalism vs. behavioural and evolutionary robotics. -/- Our preliminary claim in section 1 is that computationalism should not be identified with what we would call the “paradigm (based on the metaphor) of the computer” (in the following, PoC). PoC is the (rather vague) statement that the mind functions “as a digital computer”. Actually, PoC is a restrictive version of computationalism, and nobody ever seriously upheld it, except in some rough versions of the computational approach and in some popular discussions about it. Usually, PoC is used as a straw man in many arguments against computationalism. In section 1 we look in some detail at PoC’s claims and argue that computationalism cannot be identified with PoC. In section 2 we point out that certain anticomputationalist arguments are based on this misleading identification. In section 3 we suggest that the view of the levels of explanation proposed by David Marr could clarify certain points of the debate on computationalism. In section 4 we touch on a controversial issue, namely the possibility of developing a notion of analog computation, similar to the notion of digital computation. A short conclusion follows in section 5. (shrink)