One particular topic in the literature on Frege’s conception of sense relates to two apparently contradictory theses held by Frege: the isomorphism of thought and language on one hand and the expressibility of a thought by different sentences on the other. I will divide the paper into five sections. In (1) I introduce the problem of the tension in Frege’s thought. In (2) I discuss the main attempts to resolve the conflict between Frege’s two contradictory claims, showing what is wrong (...) with some of them. In (3), I analyze where, in Frege’s writings and discussions on sense identity, one can find grounds for two different conceptions of sense. In (4) I show how the two contradictory theses held by Frege are connected with different concerns, compelling Frege to a constant oscillation in terminology. In (5) I summarize two further reasons that prevented Frege from making the distinction between two conceptions of sense clear: (i) the antipsychologism problem and (ii) the overlap of traditions in German literature contemporary to Frege about the concept of value. I conclude with a hint for a reconstruction of the Fregean notion of ‘thought’ which resolves the contradiction between his two theses. (shrink)

The Computational Metaphor is an extremely influential notion, and more than any other trend has given rise to the field of Cognitive Science. Environmentalism is at present better formalised as a political movement than as a scientific paradigm, despite significant research by Gibson and his followers. This article attempts to address the difficult problem of synthesising these two apparently antagonistic research paradigms.

Technology explosion induced by information explosion will eventually change artifacts into intelligent autonomous agents consisting of surrogates and mediators from which humans can receive services without special training. Four potential problems might arise as a result of the paradigm shift: technology abuse, responsibility flaw, moral in crisis, and overdependence on artifacts. Although the first and second might be resolved in principle by introduction of public mediators, the rest seems beyond technical solution. Under the circumstances, a reasonable goal might be to (...) create a mutual dependency between empathy and technology: Using technology to help people cultivate empathy among people, so empathy in the society may allow people to help each other to recover from disasters beyond the scope of the assumption underlying the society of mediators. I highlight an immersive collaborative interaction environment for helping people share first-person view and its application to building empathic agents. (shrink)

The introduction of massive parallelism and the renewed interest in neural networks gives a new need to evaluate the relationship of symbolic processing and artificial intelligence. The physical symbol hypothesis has encountered many difficulties coping with human concepts and common sense. Expert systems are showing more promise for the early stages of learning than for real expertise. There is a need to evaluate more fully the inherent limitations of symbol systems and the potential for programming compared with training. This can (...) give more realistic goals for symbolic systems, particularly those based on logical foundations. (shrink)

I sketch an explanatory framework that fits a variety of contemporary research programs in cognitive science. I then investigate the scope and the implications of this framework. The framework emphasizes (a) the explanatory role played by the semantic content of cognitive representations, and (b) the important mechanistic, non-intentional dimension of cognitive explanations. I show how both of these features are present simultaneously in certain varieties of cognitive explanation. I also consider the explanatory role played by grounded representational content, that is, (...) content evaluated by appeal to its truth, falsity, accuracy, inaccuracy and other relational properties. (shrink)

Scanpaths have played an important role in classic research on reading behavior. Nevertheless, they have largely been neglected in later research perhaps due to a lack of suitable analytical tools. Recently, von der Malsburg and Vasishth proposed a new measure for quantifying differences between scanpaths and demonstrated that this measure can recover effects that were missed with the traditional eyetracking measures. However, the sentences used in that study were difficult to process and scanpath effects accordingly strong. The purpose of the (...) present study was to test the validity, sensitivity, and scope of applicability of the scanpath measure, using simple sentences that are typically read from left to right. We derived predictions for the regularity of scanpaths from the literature on oculomotor control, sentence processing, and cognitive aging and tested these predictions using the scanpath measure and a large database of eye movements. All predictions were confirmed: Sentences with short words and syntactically more difficult sentences elicited more irregular scanpaths. Also, older readers produced more irregular scanpaths than younger readers. In addition, we found an effect that was not reported earlier: Syntax had a smaller influence on the eye movements of older readers than on those of young readers. We discuss this interaction of syntactic parsing cost with age in terms of shifts in processing strategies and a decline of executive control as readers age. Overall, our results demonstrate the validity and sensitivity of the scanpath measure and thus establish it as a productive and versatile tool for reading research. (shrink)

In his recent paper, Winch attacks a group of theories he calls cognitivism. These theories agree in holding that ‘the ability to think, both consciously and subconsciously, amounts to an ability to internally manipulate symbolic representations of that which we think about.The relevance of this attack to education is that ‘Cognitivism’ supplies plausible‐looking reasons for thinking that learning can take place without instruction, practice, memorisation or training and its prestige as a theory of learning devalues those activities within education.Its rejection (...) should therefore lead us to re‐examine our need for explicit teacher‐oriented pedagogies’.Cognitivism has led to an emphasis on autonomous learning and a consequent devaluing of the role of overt teaching, ‘the active transmission of knowledge and technique by an authoritative figure’. (shrink)

Two approaches to the study of diagnostic thinking are compared, one mainly propositional, namely that of Patel and Groen (1986), the other mainly semantic, that of Lemieux and Bordage (1986). Patel and Groen analyzed the linear dimension of cardiologists' discourses while solving a case of acute bacterial endocarditis, that is, the before and after propositional rules. A secondary analysis of two of their pothophysiological protocols is done using structural semantic techniques from Lemieux and Bordage where the vertical dimension of the (...) discourses is analyzed, that is, the levels of meaning or semantic axes. Contrary to Patel and Groen's position, making an accurate diagnosis is not explained in terms of pure forward reasoning through networks of causal rules, but by means of networks of semantic qualities abstracted from the symptoms and signs. The semantic qualities operate in the clinician's mind in terms of binary oppositions (e.g., sudden-gradual, unilateral-bilateral) whereby each pair of properties constitutes a semantic axis (e.g., sudden-gradual). The successful diagnosticians are those who use the most diversified and pertinent set of semantic axes and, therefore, have a deeper representation of the problem. (shrink)

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking (...) machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models. (shrink)