Scientific knowledge grows at a phenomenal pace--but few books have had as lasting an impact or played as important a role in our modern world as The Mathematical Theory of Communication, published originally as a paper on communication theory more than fifty years ago. Republished in book form shortly thereafter, it has since gone through four hardcover and sixteen paperback printings. It is a revolutionary work, astounding in its foresight and contemporaneity. The University of Illinois Press is pleased and honored (...) to issue this commemorative reprinting of a classic. (shrink)

The paper examines the main trends in the search for a theory of general biology throughout the 20th century — the physicalization on one hand, and the semiotization on the other. These two approaches had their predecessors and were formed already in the 19th century biology, as Darwinian and Baerian biology. In theoretical biology, there are co-existing (however, asymmetrical) trends toward specifying solutions and generalizing axioms. The inclusion of the biological organism as a subject into biological theory requires an analysis (...) of the concept of scientific fact. A cross-disciplinary typology of facts on the basis of their invariant features is provided. The main periods of development of theoretical biology are briefly characterised, and the trend towards the theory of biological communication and meaning outlined. (shrink)

Many philosophers and psychologists have attempted to elucidate the nature of mental representation by appealing to notions like isomorphism or abstract structural resemblance. The ‘structural representations’ that these theorists champion are said to count as representations by virtue of functioning as internal models of distal systems. In his 2007 book, Representation Reconsidered, William Ramsey endorses the structural conception of mental representation, but uses it to develop a novel argument against representationalism, the widespread view that cognition essentially involves the manipulation of (...) mental representations. Ramsey argues that although theories within the ‘classical’ tradition of cognitive science once posited structural representations, these theories are being superseded by newer theories, within the tradition of connectionism and cognitive neuroscience, which rarely if ever appeal to structural representations. Instead, these theories seem to be explaining cognition by invoking so-called ‘receptor representations’, which, Ramsey claims, aren’t genuine representations at all—despite being called representations, these mechanisms function more as triggers or causal relays than as genuine stand-ins for distal systems. I argue that when the notions of structural and receptor representation are properly explicated, there turns out to be no distinction between them. There only appears to be a distinction between receptor and structural representations because the latter are tacitly conflated with the ‘mental models’ ostensibly involved in offline cognitive processes such as episodic memory and mental imagery. While structural representations might count as genuine representations, they aren’t distinctively mental representations, for they can be found in all sorts of non-intentional systems such as plants. Thus to explain the kinds of offline cognitive capacities that have motivated talk of mental models, we must develop richer conceptions of mental representation than those provided by the notions of structural and receptor representation. (shrink)

The mathematical theory of communication.

This article reviews eight proposed strategies for solving the Symbol Grounding Problem (SGP), which was given its classic formulation in Harnad (1990). After a concise introduction, we provide an analysis of the requirement that must be satisfied by any hypothesis seeking to solve the SGP, the zero semantical commitment condition. We then use it to assess the eight strategies, which are organised into three main approaches: representationalism, semi-representationalism and non-representationalism. The conclusion is that all the strategies are semantically committed and (...) hence that none of them provides a valid solution to the SGP, which remains an open problem. (shrink)

This article is the second step in our research into the Symbol Grounding Problem (SGP). In a previous work, we defined the main condition that must be satisfied by any strategy in order to provide a valid solution to the SGP, namely the zero semantic commitment condition (Z condition). We then showed that all the main strategies proposed so far fail to satisfy the Z condition, although they provide several important lessons to be followed by any new proposal. Here, we (...) develop a new solution of the SGP. It is called praxical in order to stress the key role played by the interactions between the agents and their environment. It is based on a new theory of meaning—Action-based Semantics (AbS)—and on a new kind of artificial agents, called two-machine artificial agents (AM²). Thanks to their architecture, AM2s implement AbS, and this allows them to ground their symbols semantically and to develop some fairly advanced semantic abilities, including the development of semantically grounded communication and the elaboration of representations, while still respecting the Z condition. (shrink)

Hilary Putnam has argued that computational functionalism cannot serve as a foundation for the study of the mind, as every ordinary open physical system implements every finite-state automaton. I argue that Putnam's argument fails, but that it points out the need for a better understanding of the bridge between the theory of computation and the theory of physical systems: the relation of implementation. It also raises questions about the class of automata that can serve as a basis for understanding the (...) mind. I develop an account of implementation, linked to an appropriate class of automata, such that the requirement that a system implement a given automaton places a very strong constraint on the system. This clears the way for computation to play a central role in the analysis of mind. (shrink)

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem : How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their shapes, be grounded (...) in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and categorical representations, which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their categorical representations. Higher-order symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations. Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic module, however; the symbolic functions would emerge as an intrinsically dedicated symbol system as a consequence of the bottom-up grounding of categories ' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded. (shrink)

"This is an important new Cummins work.

An interesting feature of some sets of representations is that their structure mirrors the structure of the items they represent. Founding an account of representational content on isomorphism, homomorphism or structural resemblance has proven elusive, however, largely because these relations are too liberal when the candidate structure over representational vehicles is unconstrained. Furthermore, in many cases where there is a clear isomorphism, it is not relied on in the way the representations are used. That points to a potential resolution: that (...) an isomorphism must be used, hence usable, if it is to be an ingredient in a theory of content. This paper argues that the class of exploitable isomorphisms can indeed play a content-constituting role. (shrink)

It is argued that a number of important, and seemingly disparate, types of representation are species of a single relation, here called structural representation, that can be described in detail and studied in a way that is of considerable philosophical interest. A structural representation depends on the existence of a common structure between a representation and that which it represents, and it is important because it allows us to reason directly about the representation in order to draw conclusions about the (...) phenomenon that it depicts. The present goal is to give a general and precise account of structural representation, then to use that account to illuminate several problems of current philosophical interest — including some that do not initially seem to involve representation at all. In particular, it is argued that ontological reductions (like that of the natural numbers to sets), compositional accounts of semantics, several important sorts of mental representation, and (perhaps) possible worlds semantics for intensional logics are all species of structural representation and are fruitfully studied in the framework developed here. (shrink)

Looks at accounts by Locke, Fodor, Dretske, and Millikan concerning the nature of mental representation, and discusses connectionism and representation.

"Eco wittily and enchantingly develops themes often touched on in his previous works, but he delves deeper into their complex nature... this collection can be read with pleasure by those unversed in semiotic theory." —Times Literary Supplement.

Fundamental turns in biological understanding can be interpreted as replacements of deep models that organise the biological knowledge. Three deep models distinguished here are a holistic ladder model that sees all levels of nature being complete (from Aristotle to the 18th century), a modernist tree model that emphasises progress and evolution (from Enlightenment to the recent times), and a web model that evaluates diversity (since the 20th century). The turn from the tree model to the web model in biology includes (...) (1) a transfer from modern to postmodern approaches, (2) a shift of semiotic threshold to the border of life, and (3) building the semiotic models of living systems, i.e., the rise of biosemiotics. (shrink)

Any creature that must move around in its environment to find nutrients and mates, in order to survive and reproduce, faces the problem of sensorimotor control. A solution to this problem requires an on-board control mechanism that can shape the creature’s behaviour so as to render it “appropriate” to the conditions that obtain. There are at least three ways in which such a control mechanism can work, and Nature has exploited them all. The first and most basic way is for (...) a creature to bump into the things in its environment, and then, depending on what has been encountered, seek to modify its behaviour accordingly. Such an approach is risky, however, since some things in the environment are distinctly unfriendly. A second and better way, therefore, is for a creature to exploit ambient forms of energy that carry information about the distal structure of the environment. This is an improvement on the first method since it enables the creature to respond to the surroundings without actually bumping into anything. Nonetheless, this second method also has its limitations, one of which is that the information conveyed by such ambient energy is often impoverished, ambiguous and intermittent. (shrink)

This paper traces the application of information theory to philosophical problems of mind and meaning from the earliest days of the creation of the mathematical theory of communication. The use of information theory to understand purposive behavior, learning, pattern recognition, and more marked the beginning of the naturalization of mind and meaning. From the inception of information theory, Wiener, Turing, and others began trying to show how to make a mind from informational and computational materials. Over the last 50 years, (...) many philosophers saw different aspects of the naturalization of the mind, though few saw at once all of the pieces of the puzzle that we now know. Starting with Norbert Wiener himself, philosophers and information theorists used concepts from information theory to understand cognition. This paper provides a window on the historical sequence of contributions made to the overall project of naturalizing the mind by philosophers from Shannon, Wiener, and MacKay, to Dennett, Sayre, Dretske, Fodor, and Perry, among others. At some time between 1928 and 1948, American engineers and mathematicians began to talk about `Theory of Information' and `Information Theory,' understanding by these terms approximately and vaguely a theory for which Hartley's `amount of information' is a basic concept. I have been unable to find out when and by whom these names were first used. Hartley himself does not use them nor does he employ the term `Theory of Transmission of Information,' from which the two other shorter terms presumably were derived. It seems that Norbert Wiener and Claude Shannon were using them in the Mid-Forties. (shrink)

In this essay I shall focus on the adoption of the Semantic Approach by structural realists, including myself, who have done so on the grounds that it wears its structuralist sympathies on its sleeve. Despite this, the SA has been identified as standing in tension with the ontological commitments of the so-called ’ontic’ form of this view and so I shall explore that tension before discussing the usefulness of the SA in framing scientific representation and concluding with a discussion of (...) the implications of the ontological status of theories and models themselves. (shrink)

While neuroscientists often characterize brain activity as representational, many philosophers have construed these accounts as just theorists’ glosses on the mechanism. Moreover, philosophical discussions commonly focus on finished accounts of explanation, not research in progress. I adopt a different perspective, considering how characterizations of neural activity as representational contributes to the development of mechanistic accounts, guiding the investigations neuroscientists pursue as they work from an initial proposal to a more detailed understanding of a mechanism. I develop one illustrative example involving (...) research on the information-processing mechanisms mammals employ in navigating their environments. This research was galvanized by the discovery in the 1970s of place cells in the hippocampus. This discovery prompted research in what the activity of these cells represents and how place representations figure in navigation. It also led to the discovery of a host of other types of neurons—grid cells, head-direction cells, boundary cells—that carry other types of spatial information and interact with place cells in the mechanism underlying spatial navigation. As I will try to make clear, the research is explicitly devoted to identifying representations and determining how they are constructed and used in an information processing mechanism. Construals of neural activity as representations are not mere glosses but are characterizations to which neuroscientists are committed in the development of their explanatory accounts. (shrink)

In Representation Reconsidered , William Ramsey suggests that the notion of structural representation is posited by classical theories of cognition, but not by the ‘newer accounts’ (e.g. connectionist modeling). I challenge the assertion about the newer accounts. I argue that the newer accounts also posit structural representations; in fact, the notion plays a key theoretical role in the current computational approaches in cognitive neuroscience. The argument rests on a close examination of computational work on the oculomotor system.

Cognitive representation is the single most important explanatory notion in the sciences of the mind and has served as the cornerstone for the so-called 'cognitive revolution'. This book critically examines the ways in which philosophers and cognitive scientists appeal to representations in their theories, and argues that there is considerable confusion about the nature of representational states. This has led to an excessive over-application of the notion - especially in many of the fresher theories in computational neuroscience. Representation Reconsidered shows (...) how psychological research is actually moving in a non-representational direction, revealing a radical, though largely unnoticed, shift in our basic understanding of how the mind works. (shrink)

What makes our brain a brain? This is the central question posited in Unlocking the Brain. By providing a fascinating venture into different territories of neuroscience, psychiatry, and philosophy, the author takes a novel exploration of the brain's resting state in the context of the neural code, and its ability to yield consciousness.

The existence of different types of semiosis has been recognized, so far, in two ways. It has been pointed out that different semiotic features exist in different taxa and this has led to the distinction between zoosemiosis, phytosemiosis, mycosemiosis, bacterial semiosis and the like. Another type of diversity is due to the existence of different types of signs and has led to the distinction between iconic, indexical and symbolic semiosis. In all these cases, however, semiosis has been defined by the (...) Peirce model, i.e., by the idea that the basic structure is a triad of ‘sign, object and interpretant’, and that interpretation is an essential component of semiosis. This model is undoubtedly applicable to animals, since it was precisely the discovery that animals are capable of interpretation that allowed Thomas Sebeok to conclude that they are also capable of semiosis. Unfortunately, however, it is not clear how far the Peirce model can be extended beyond the animal kingdom, and we already know that we cannot apply it to the cell. The rules of the genetic code have been virtually the same in all living systems and in all environments ever since the origin of life, which clearly shows that they do not depend on interpretation. Luckily, it has been pointed out that semiosis is not necessarily based on interpretation and can be defined exclusively in terms of coding. According to the ‘code model’, a semiotic system is made of signs, meanings and coding rules, all produced by the same codemaker, and in this form it is immediately applicable to the cell. The code model, furthermore, allows us to recognize the existence of many organic codes in living systems, and to divide them into two main types that here are referred to as manufacturing semiosis and signalling semiosis. The genetic code and the splicing codes, for example, take part in processes that actually manufacture biological objects, whereas signal transduction codes and compartment codes organize existing objects into functioning supramolecular structures. The organic codes of single cells appeared in the first three billion years of the history of life and were involved either in manufacturing semiosis or in signalling semiosis. With the origin of animals, however, a third type of semiosis came into being, a type that can be referred to as interpretive semiosis because it became closely involved with interpretation. We realize in this way that the contribution of semiosis to life was far greater than that predicted by the Peirce model, where semiosis is always a means of interpreting the world. Life is essentially about three things: (1) it is about manufacturing objects, (2) it is about organizing objects into functioning systems, and (3) it is about interpreting the world. The idea that these are all semiotic processes, tells us that life depends on semiosis much more deeply and extensively than we thought. We realize in this way that there are three distinct types of semiosis in Nature, and that they gave very different contributions to the origin and the evolution of life. (shrink)