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- C. Franklin Boyle (2001). Transduction and Degree of Grounding. Psycoloquy 12 (36).While I agree in general with Stevan Harnad's symbol grounding proposal, I do not believe "transduction" (or "analog process") PER SE is useful in distinguishing between what might best be described as different "degrees" of grounding and, hence, for determining whether a particular system might be capable of cognition. By 'degrees of grounding' I mean whether the effects of grounding go "all the way through" or not. Why is transduction limited in this regard? Because transduction is a physical process which does not speak to the issue of representation, and, therefore, does not explain HOW the informational aspects of signals impinging on sensory surfaces become embodied as symbols or HOW those symbols subsequently cause behavior, both of which, I believe, are important to grounding and to a system's cognitive capacity. Immunity to Searle's Chinese Room (CR) argument does not ensure that a particular system is cognitive, and whether or not a particular degree of groundedness enables a system to pass the Total Turing Test (TTT) may never be determined.Reading list | Discuss | Edit | Categorize |My bibliography
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The Chinese room argument has presented a persistent headache in the search for Artificial Intelligence. Since it first appeared in the literature, various interpretations have been made, attempting to understand the problems posed by this thought experiment. Throughout all this time, some researchers in the Artificial Intelligence community have seen Symbol Grounding as proposed by Harnad as a solution to the Chinese room argument. The main thesis in this paper is that although related, these two issues present different problems in the framework presented by Harnad himself. The work presented here attempts to shed some light on the relationship between John Searle’s intentionality notion and Harnad’s Symbol Grounding Problem.
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| | Other links: dx.doi.org springerlink.com | Scholar | At my library | More options ... "Symbol Grounding" is beginning to mean too many things to too many people. My own construal has always been simple: Cognition cannot be just computation, because computation is just the systematically interpretable manipulation of meaningless symbols, whereas the meanings of my thoughts don't depend on their interpretability or interpretation by someone else. On pain of infinite regress, then, symbol meanings must be grounded in something other than just their interpretability if they are to be candidates for what is going on in our heads. Neural nets may be one way to ground the names of concrete objects and events in the capacity to categorize them (by learning the invariants in their sensorimotor projections). These grounded elementary symbols could then be combined into symbol strings expressing propositions about more abstract categories. Grounding does not equal meaning, however, and does not solve any philosophical problems.
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| | Other links: eprints.ecs.soton.ac.uk cogprints.org cogsci.soton.ac.uk ecs.soton.ac.uk | Scholar | More options ... Can someone be reasonable or justified in accepting a specific moral judgment not based on the prior acceptance of a general exceptioness moral principle, where acceptance of a general principle might be tacit or implicit and might not be expressible in language? This issue is an instance of a wider issue about direct or transductive inference. Developments in statistical learning theory show that such an inference can be more effective than alternative methods using inductive generalization and so can be reasonable. This result carries over to moral transduction, although it is a difficult empirical issue whether people actually engage in any sort of transduction, including moral transduction.
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| | Other links: blackwell-synergy.com interscience.wiley.com blackwell-synergy.com dx.doi.org | Scholar | At my library | More options ... In this paper we consider the importance of using a humanoid physical form for a certain proposed kind of robotics, that of theory grounding. Theory grounding involves grounding the theory skills and knowledge of an embodied artificially intelligent (AI) system by developing theory skills and knowledge from the bottom up. Theory grounding can potentially occur in a variety of domains, and the particular domain considered here is that of language. Language is taken to be another problem space in which a system can explore and discover solutions. We argue that because theory grounding necessitates robots experiencing domain information, certain behavioral-form aspects, such as abilities to socially smile, point, follow gaze, and generate manual gestures, are necessary for robots grounding a humanoid theory of language.
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| | Other links: cogprints.org | Scholar | More options ... The primary goal of this chapter is to set out and clarify some of the central issues and disputes concerning grounding (alternatively, the in virtue of relation, priority, metaphysical explanation, and so on). I begin by introducing a taxonomy of positions that proceeds upon a cluster of related issues including, for example, whether our talk of grounding in philosophical discourse is univocal. Then I consider the logical form of grounding statements as well as the structural principles that govern grounding. Next, I take up the matter of how the notions of grounding, modality, and reduction interact. I close with a brief discussion of the grounds for true grounding claims.
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| | Scholar | More options ... It is unlikely that the systematic, compositional properties of formal symbol systems -- i.e., of computation -- play no role at all in cognition. However, it is equally unlikely that cognition is just computation, because of the symbol grounding problem (Harnad 1990): The symbols in a symbol system are systematically interpretable, by external interpreters, as meaning something, and that is a remarkable and powerful property of symbol systems. Cognition (i.e., thinking), has this property too: Our thoughts are systematically interpretable by external interpreters as meaning something. However, unlike symbols in symbol systems, thoughts mean what they mean autonomously: Their meaning does not consist of or depend on anyone making or being able to make any external interpretations of them at all. When I think "the cat is on the mat," the meaning of that thought is autonomous; it does not depend on YOUR being able to interpret it as meaning that (even though you could interpret it that way, and you would be right).
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| Discuss | Edit | Categorize | My bibliography | Export citation | Other links: cogprints.org eprints.ecs.soton.ac.uk cogprints.soton.ac.uk ieeexplore.ieee.org cogsci.soton.ac.uk ecs.soton.ac.uk citebase.eprints.org | Scholar | At my library | More options ...
| | Other links: cogprints.org eprints.ecs.soton.ac.uk cogprints.soton.ac.uk ieeexplore.ieee.org cogsci.soton.ac.uk ecs.soton.ac.uk citebase.eprints.org | Scholar | At my library | More options ... Harnad's main argument can be roughly summarised as follows: due to Searle's Chinese Room argument, symbol systems by themselves are insufficient to exhibit cognition, because the symbols are not grounded in the real world, hence without meaning. However, a symbol system that is connected to the real world through transducers receiving sensory data, with neural nets translating these data into sensory categories, would not be subject to the Chinese Room argument. Harnad's article is not only the starting point for the present debate, but is also a contribution to a longlasting discussion about such questions as: Can a computer think? If yes, would this be solely by virtue of its program? Is the Turing Test appropriate for deciding whether a computer thinks?
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| | Other links: cogprints.org | Scholar | At my library | More options ... The paper presents a paradoxical feature of computational systems that suggests that computationalism cannot explain symbol grounding. If the mind is a digital computer, as computationalism claims, then it can be computing either over meaningful symbols or over meaningless symbols. If it is computing over meaningful symbols its functioning presupposes the existence of meaningful symbols in the system, i.e. it implies semantic nativism. If the mind is computing over meaningless symbols, no intentional cognitive processes are available prior to symbol grounding. In this case, no symbol grounding could take place since any grounding presupposes intentional cognitive processes. So, whether computing in the mind is over meaningless or over meaningful symbols, computationalism implies semantic nativism.
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| | Other links: typos.de springerlink.com dx.doi.org | Scholar | At my library | More options ... In this commentary on Harnad's "Grounding Symbols in the Analog World with Neural Nets: A Hybrid Model," the issues of symbol grounding and analog (continuous) computation are separated, it is argued that symbol graounding is as important an issue for analog cognitive models as for digital (discrete) models. The similarities and differences between continuous and discrete computation are discussed, as well as the grounding of continuous representations. A continuous analog of the Chinese Room is presented.
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| Discuss | Edit | Categorize | My bibliography | Export citation | Other links: citeseer.ist.psu.edu cogprints.org psycprints.ecs.soton.ac.uk cogsci.soton.ac.uk ecs.soton.ac.uk | Scholar | At my library | More options ...
| | Other links: citeseer.ist.psu.edu cogprints.org psycprints.ecs.soton.ac.uk cogsci.soton.ac.uk ecs.soton.ac.uk | Scholar | At my library | More options ... The issue of symbol grounding is not essentially different in analog and digital computation. The principal difference between the two is that in analog computers continuous variables change continuously, whereas in digital computers discrete variables change in discrete steps (at the relevant level of analysis). Interpretations are imposed on analog computations just as on digital computations: by attaching meanings to the variables and the processes defined over them. As Harnad (2001) claims, states acquire intrinsic meaning through their relation to the real (physical) environment, for example, through transduction. However, this is independent of the question of the continuity or discreteness of the variables or the transduction processes.
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| | Scholar | More options ... Discussion of C. Franklin Boyle, Transduction and degree of grounding
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