Intermediate constructs are required as bridges between complex behaviors and realistic models of neural circuitry. For cognitive scientists in general, schemas are the appropriate functional units; brain theorists can work with neural layers as units intermediate between structures subserving schemas and small neural circuits.After an account of different levels of analysis, we describe visuomotor coordination in terms of perceptual schemas and motor schemas. The interest of schemas to cognitive science in general is illustrated with the example of perceptual schemas in (...) high-level vision and motor schemas in the control of dextrous hands.Rana computatrix, the computational frog, is introduced to show how one constructs an evolving set of model families to mediate flexible cooperation between theory and experiment. Rana computatrix may be able to do for the study of the organizational principles of neural circuitry what Aplysia has done for the study of subcellular mechanisms of learning. Approach, avoidance, and detour behavior in frogs and toads are analyzed in terms of interacting schemas. Facilitation and prey recognition are implemented as tectal-pretectal interactions, with the tectum modeled by an array of tectal columns. We show how layered neural computation enters into models of stereopsis and how depth schemas may involve the interaction of accommodation and binocular cues in anurans. (shrink)

Those who believe that explicitly Christian thinking is possible in the scientific disciplines tend to assume that it must be antithetical to the world’s thinking. Based on some of the author’s experience, this article examines a different approach, in which Christian thinking is used to account for and enrich the world’s thinking by transplanting it from its current ground-motive into the arguably more fertile soil of the creation-fall-redemption ground-motive. The article shows how Dooyeweerd’s version of Christian thinking has been employed (...) in two areas of thinking in information systems : thinking about the nature of computers and information, with the artificial intelligence question of whether computer is like human being soft systems methodology, by which perspectives on ‘human activity systems’ are orchestrated into new learning and plans. In both areas, the original ideas are accounted for, given philosophical underpinning, reinterpreted and enriched. These two show that Dooyeweerd’s philosophy can be equally useful in thinking grounded in both positivist and interpretivist cultures. (shrink)

It is argued that “human-centredness” will be an important characteristic of systems that learn tasks from human users, as the difficulties in inductive inference rule out learning without human assistance. The aim of “programming by example” is to create systems that learn how to perform tasks from their human users by being shown examples of what is to be done. Just as the user creates a learning environment for the system, so the system provides a teaching opportunity for the user, (...) and emphasis is placed as much on facilitating successful teaching as on incorporating techniques of machine learning. If systems can “learn” repetitive tasks, their users will have the power to decide for themselves which parts of their jobs should be automated, and teach the system how to do them — reducing their dependence on intermediaries such as system designers and programmers.This paper presents principles for programming by example derived from experience in creating four prototype learners: for technical drawing, text editing, office tasks, and robot assembly. A teaching metaphor (a) enables the user to demonstrate a task by performing it manually, (b) helps to explain the learner's limited capabilities in terms of a persona, and (c) allows users to attribute intentionality. Tasks are represented procedurally, and augmented with constraints. Suitable mechanisms for attention focusing are necessary in order to control inductive search. Hidden features of a task should be made explicit so that the learner need not embark on the huge search entailed by hypothesizing missing steps. (shrink)

The problem of semantic content is the problem of explicating those features of brain processes by virtue of which they may properly be thought to possess meaning or reference. This paper criticizes the account of semantic content associated with fodor's version of cognitive science, And offers an alternative account based on mathematical communication theory. Its key concept is that of a neuronal representation maintaining a high-Level of mutual information with a designated external state of affairs under changing conditions of perceptual (...) presentation. (shrink)

Experiences of qualia, subjective sensory-like aspects of stimuli, are central to imagistic representation. Following Raffman , qualia are considered to reflect experiential knowledge distinct from descriptive, abstract, and propositional knowledge; following Jackendoff , objective neural activity is distinguished from subjective experience. It is argued that descriptive physical knowledge does not provide an adequate accounting of qualia, and philosophical scenarios such as the Turing test and the Chinese Room are adapted to demonstrate inadequacies of accounts of cognition that ignore subjective experience. (...) Arguments by Dennett and others that qualia do not exist or that qualia do not provide additional explanatory power are addressed, and it is suggested that consideration of qualia is necessary in order to explain objective behavior. The hypotheses of functional equivalence, second-order isomorphism, and psychophysical complementarity between imagery and perception are discussed, and the ability of analog and schematic models of imagery to account for qualia is examined. (shrink)