In his target article Page proposes a definition of the term “localist.” In this commentary I argue that his definition does not serve to make a principled distinction, as the inclusion of vague terms make it susceptible to some problematic counterexamples.

Connectionism is a style of modeling based upon networks of interconnected simple processing devices. This style of modeling goes by a number of other names too. Connectionist models are also sometimes referred to as 'Parallel Distributed Processing' (or PDP for short) models or networks.1 Connectionist systems are also sometimes referred to as 'neural networks' (abbreviated to NNs) or 'artificial neural networks' (abbreviated to ANNs). Although there may be some rhetorical appeal to this neural nomenclature, it is in fact misleading as (...) connectionist networks are commonly significantly dissimilar to neurological systems. For this reason, I will avoid using this terminology, other than in direct quotations. Instead, I will follow the practice I have adopted above and use 'connectionist' as my primary term for systems of this kind. (shrink)

Clark & Thornton are too hasty in their dismissal of uninformed learning; nonmonotonic processing units show considerable promise on type-2 tasks. I describe a simulation which succeeds on a “pure” type-2 problem. Another simulation challenges Clark & Thornton 's claims about the serendipitous nature of solutions to type-2 problems.

Ancient treatise on Sankhya philosophy; Sanskrit text with English and Oriya translation and interpretation.

Connectionist research first emerged in the 1940s. The first phase of connectionism attracted a certain amount of media attention, but scant philosophical interest. The phase came to an abrupt halt, due to the efforts of Minsky and Papert (1969), when they argued for the intrinsic limitations of the approach. In the mid-1980s connectionism saw a resurgence. This marked the beginning of the second phase of connectionist research. This phase did attract considerable philosophical attention. It was of philosophical interest, as it (...) offered a way of counteracting the conceptual ties to the philosophical traditions of atomism, rationalism, logic, nativism, rule realism and a concern with the role symbols play in human cognitive functioning, which was prevalent as a consequence of artificial intelligence research. The surge in philosophical interest waned, possibly in part due to the efforts of some traditionalists and the so-called black box problem. Most recently, what may be thought of as a third phase of connectionist research, based on so-called deep learning methods, is beginning to show some signs of again exciting philosophical interest. (shrink)

In 1988, Smolensky proposed that connectionist processing systems should be understood as operating at what he termed the `subsymbolic' level. Subsymbolic systems should be understood by comparing them to symbolic systems, in Smolensky's view. Up until recently, there have been real problems with analyzing and interpreting the operation of connectionist systems which have undergone training. However, recently published work on a network trained on a set of logic problems originally studied by Bechtel and Abrahamsen (1991) seems to offer the potential (...) to provide a detailed, empirically based answer to questions about the nature of subsymbols. In this paper, a network analysis procedure and the results obtained using it are discussed. This provides the basis for an insight into the nature of subsymbols, which is surprising. (shrink)

Since the emergence of what Fodor and Pylyshyn (1988) call 'new connectionism', there can be little doubt that connectionist research has become a significant topic for discussion in the Philosophy of Cognitive Science and the Philosophy of Mind. In addition to the numerous papers on the topic in philosophical journals, almost every recent book in these areas contain at least a brief reference to, or discussion of, the issues raised by connectionist research (see Sterelny 1990, Searle, 1992, and O Nualláin, (...) 1995, for example). Other texts have focused almost exclusively upon connectionist issues (see Clark, 1993, Bechtel and Abrahamsen, 1991 and Lloyd, 1989, for example). Regrettably the discussions of connectionism found in the philosophical literature suffer from a number of deficiencies. My purpose in this paper is to highlight one particular problem and attempt to take a few steps to remedy the situation. (shrink)

Hagiography of Sankaracarya, the exponent of Advaita philosophy.

В работе проведен сравнительный анализ терминологии грамоты и статута, выявлены и сопоставлены общие и родственные термины в контексте законодательств. Для специалистов.

According to the standard (recent) history of connectionism (see for example the accounts offered by Hecht-Nielsen (1990: pp. 14-19) and Dreyfus and Dreyfus (1988), or Papert's (1988: pp. 3-4) somewhat whimsical description), in the early days of Classical Computational Theory of Mind (CCTM) based AI research, there was also another allegedly distinct approach, one based upon network models. The work on network models seems to fall broadly within the scope of the term 'connectionist' (see Aizawa 1992), although the term had (...) yet to be coined at the time. These two approaches were "two daughter sciences" according to Papert (1988: p. 3). The fundamental difference between these two 'daughters', lay (according to Dreyfus and Dreyfus (1988: p. 16)) in what they took to be the paradigm of intelligence. Whereas the early connectionists took learning to be fundamental, the traditional school concentrated upon problem solving. (shrink)

In this paper the issue of drawing inferences about biological cognitive systems on the basis of connectionist simulations is addressed. In particular, the justification of inferences based on connectionist models trained using the backpropagation learning algorithm is examined. First it is noted that a justification commonly found in the philosophical literature is inapplicable. Then some general issues are raised about the relationships between models and biological systems. A way of conceiving the role of hidden units in connectionist networks is then (...) introduced. This, in combination with an assumption about the way evolution goes about solving problems, is then used to suggest a means of justifying inferences about biological systems based on connectionist research. (shrink)

The notion of a ‘symbol’ plays an important role in the disciplines of Philosophy, Psychology, Computer Science, and Cognitive Science. However, there is comparatively little agreement on how this notion is to be understood, either between disciplines, or even within particular disciplines. This paper does not attempt to defend some putatively ‘correct’ version of the concept of a ‘symbol.’ Rather, some terminological conventions are suggested, some constraints are proposed and a taxonomy of the kinds of issue that give rise to (...) disagreement is articulated. The goal here is to provide something like a ‘geography’ of the various notions of ‘symbol’ that have appeared in the various literatures, so as to highlight the key issues and to permit the focusing of attention upon the important dimensions. In particular, the relationship between ‘tokens’ and ‘symbols’ is addressed. The issue of designation is discussed in some detail. The distinction between simple and complex symbols is clarified and an apparently necessary condition for a system to be potentially symbol, or token bearing, is introduced. (shrink)

Aphoristic work on Sankhya philosophy with Sanskrit commentary and Hindi translation of Sāṅkhyaśāstra, Maithili commentary by Durgādhara Jhā.

Work on Sankhya system in Hindu philosophy; includes commentaries.

This introduction begins by posing the question that this Special Issue addresses and briefly considers historical precedents and why the issue is important. The discussion then moves on to the consideration of important milestones in the history of computing, up until the present time. A brief specification of the essential components of computational systems is then offered. The final section introduces the papers that are included in this volume.

One of the most important theoretical and ideological tasks of Marxist philosophy is the critical study of the philosophical thought of the West. In the second half of the 1970s and beginning of the 1980s, the ideological struggle on the international arena entered a new stage. It was characterized by the turn of the forces of imperialist reaction away from the politics of detente to the politics of the "cold war," to the active opposition to the forces of peace, democracy, (...) and socialism. The struggle of ideas has swung back and forth in the context of, on the one hand, a resurgence of reactionary anticommunist tendencies, and the stimulation and expansion of antimilitary movements and the struggles of the peoples for peace and socialism on the other. (shrink)

Nietzsche, Friedrich Wilhelm, 1844-1900; criticism and interpretation; Human; Alienation; philosophical aspects; Philosophy, Modern; 19th century.

Berkeley [Minds Machines 10 (2000) 1] described a methodology that showed the subsymbolic nature of an artificial neural network system that had been trained on a logic problem, originally described by Bechtel and Abrahamsen [Connectionism and the mind. Blackwells, Cambridge, MA, 1991]. It was also claimed in the conclusion of this paper that the evidence was suggestive that the network might, in fact, count as a symbolic system. Dawson and Piercey [Minds Machines 11 (2001) 197] took issue with this (...) latter claim. They described some lesioning studies that they argued showed that Berkeley’s (2000) conclusions were premature. In this paper, these lesioning studies are replicated and it is shown that the effects that Dawson and Piercey rely upon for their argument are merely an artifact of a threshold function they chose to employ. When a threshold function much closer to that deployed in the original studies is used, the significant effects disappear. (shrink)

The psychological state and neural correlates of 19 women undergoing normal childbirth were studied. Frequent occurence of nonordinary psychological phenomena was traced back in 6 subjects, occurring in active and passive alertness, as well as hypnagogic/hypnopompic periods, and in dreaming, during the late period of pregnancy, giving birth, and the period of 2-4 days post partull. The brain activity of the aforementioned subgroup during this time was characterized primarily by general activation of the right hemisphere in the bandpass of infraslow (...) electrical processes and by more localized EEG activation. The implications of the data for research on gender-specific altered states of consciousness are discussed. (shrink)

There is widespread belief that connectionist networks are dramatically different from classical or symbolic models. However, connectionists rarely test this belief by interpreting the internal structure of their nets. A new approach to interpreting networks was recently introduced by Berkeley et al. (1995). The current paper examines two implications of applying this method: (1) that the internal structure of a connectionist network can have a very classical appearance, and (2) that this interpretation can provide a cognitive theory that cannot (...) be dismissed as a mere implementation. (shrink)

Treatise with auto-commentary on Dvaita philosophy.