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- Allen Newell (1982). The Knowledge Level. Artificial Intelligence 18:81-132.
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This paper presents a skill learning model CLARION. Different from existing models of mostly high-level skill learning that use a top-down approach (that is, turning declarative knowledge into procedural knowledge through practice), we adopt a bottom-up approach toward low-level skill learning, where procedural knowledge develops first and declarative knowledge develops later. Our model is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line reactive learning. It adopts a two-level dual-representation framework (Sun, 1995), with a combination of localist and distributed representation. We compare the model with human data in a minefield navigation task, demonstrating some match between the model and human data in several respects. © 2001 Cognitive Science Society, Inc. All rights reserved.
The author applies an economic theory of ordinary knowledgestreet-level epistemologyto the popular understanding of science. Street-level theory is essentially economic and pragmatic. If it is very costly to learn something, you are less likely to learn it. If you need to know it, you are more likely to find out about it (although what you find out might be wrong). For most of what you know, you essentially rely on others as sources (some of these others might be "experts," but many are not). In general, the ordinary person does not need to know modern physics and cannot be expected to. But most of us generally need medical knowledge on occasion, and we can be expected to go in quest of it. Our primary task in seeking medical knowledge, however, is to settle on whom we count as relevant experts. Key Words: knowledge epistemology scientific knowledge ordinary knowledge.
This paper argues that Sosa’s virtue perspectivism fails to combine satisfactorily internalist and externalist features in a single theory. Internalism and externalism are reconciled at the price of creating a Gettier problem at the level of “reflective” or second-order knowledge. The general lesson to be learned from the critique of virtue perspectivism is that internalism and externalism cannot be combined by bifurcating justification and knowledge into an object-level and a meta-level and assigning externalism and internalism to different levels.
Negrotti's theory of the artificial is based on the fundamental assumption that the human being cannot select more than one observation level per unit of time. Since this assumption has important consequences for the theory of knowledge â knowledge cannot be synthesised but only further differentiated â its plausibility is tested against two aspects that characterise any theory of knowledge: knowledge production and knowledge application. The way in which the human being produces and applies knowledge is analysed, and a model of mind based on the transitoriness of its elements is proposed. The analysis confirms that only one observation level can be selected per unit of time.
Belief is considered a kind of performance, which attains one level of success if it is true (or accurate), a second level if competent (or adroit), and a third if true because competent (or apt). Knowledge on one level (the animal level) is apt belief. The epistemic normativity constitutive of such knowledge is thus a kind of performance normativity. A problem is posed for this account by the fact that suspension of belief seems to fall under the same sort of epistemic normativity as does belief itself, yet to suspend is of course precisely not to perform, certainly not with the aim of truth. The paper takes up this problem, and proposes a solution that distinguishes levels of performance norrmativity, including a first order where execution competence is in play, and a second order where the performer must assess the risks attendant on issuing a first-order performance. This imports a level of reflective knowledge that ascends above the animal level.
The purpose of the paper is to explore, from an assessment viewpoint, the following ideas. Economics, as a social science, has always considered sets of individuals with assumed characteristics (namely, the level of knowledge), although in an implicit way, in most of the cases. In this sense, an influential approach in economics assumed that society, as a global set of individuals, was characterized by a certain level of knowledge, that, indeed, could be associated with one of its representative agents. In fact, an attentive recall of the evolution of these matters in economics will immediately recognize that, since the very first economic models of the government, it was assumed that the level of knowledge of society, represented by a set of voters, was not the same as one of the agents elected, i.e., the government. The irrelevance of the difference in the level of knowledge of economic agents was soon abandoned after some seminal works of Hayek and Friedman. More recently, the viewpoint of economics has changed, by focusing on the characteristics (e.g., knowledge) of individuals, who may interact in the subsets of the society. Given the close connection with the assumed level of knowledge, it is clearly relevant from this point of view, to distinguish adaptive behavior from the rational one by people, as well as the full rational from the bounded rationality behavior. Quite recent developments in the economics of knowledge, i.e., the so-called learning models, have been considered as more realistic approaches to model the process by which individuals acquire knowledge, for instance, from other individuals who are, themselves, acquiring knowledge.
Basic processes of perception should be cognitively impenetrable so that they are not prey to momentary changes of belief. That said, how does low level vision interact with knowledge to allow recognition? Much more needs to be known about the products of low level vision than that they represent the geometric layout of the world.
In this paper, I define tacit knowledge as a kind of causal-explanatory structure, mirroring the derivational structure in the theory that is tacitly known. On this definition, tacit knowledge does not have to be explicitly represented. I then take the notion of a modular theory, and project the idea of modularity to several different levels of description: in particular, to the processing level and the neurophysiological level. The fundamental description of a connectionist network lies at a level between the processing level and the physiological level. At this level, connectionism involves a characteristic departure from modularity, and a correlative absence of syntactic structure. This is linked to the fact that tacit knowledge descriptions of networks are only approximately true. A consequence is that strict causal systematicity in cognitive processes poses a problem for the connectionist programme.
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