Toward a Theory of Complex and Cognitive Systems (original) (raw)
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A Theory of the Mind as a Complex System
Current Research in Psychology, 2012
Five principles of skill acquisition are presented based on a review of research on human learning and expertise. Essentially these principles state that practice leads to faster and more efficient uses of knowledge. This enables faster performance and results in less demand on mental resources. In turn these outcomes enable higher level behaviours to be attempted. Ultimately skills are developed through refinement of many component processes. A theory of the mind is proposed that borrows from theories of complex adaptive systems. In this theory, the mind is conceived of as consisting of agents that compete for resources associated with processing information. The nature of this competition is similar to that observed in physical and biological systems in that agents survive or disappear depending on their usefulness. This theory is shown to be capable of explaining the five principles of skill acquisition, without these principles being explicitly built into the theory. Implications for other theories of skill acquisition are considered.
On the role of general system theory in the cognitive process
The cognitive process of an open goal-seeking system can be analyzed in terms of its interaction with its environment. From the point of view of the system, this interaction means the appearance of problem situations. Some of these problem situations become actual problems to be solved by the system and others do not. Therefore the cognitive process can be analyzed in terms of the functioning of a complex problem-solving system, i.e., the cognitive process is a complicated problem-solving process which anticipates the sequential solution of problems that require various kinds of problem-solving systems. The purpose of the present study is to describe the various problem types and to analyze the requirements of their individual adequate problem-solving systems. The role that the General Systems Theory (GST) plays in the working of the individual solving systems will be analyzed here. 1. Problem-solving The functioning of an open, goal-seeking system can be analyzed in terms of its interaction with its environment. The environment of a system is here understood to be a universe that, being a logical system, can be regarded as a set of statements. The environment therefore acts on the system via statements. Depending on the corpus of knowledge embodied in the system, a statement may be comprehensible or incomprehensible. Statements of the latter kind are what we call problems 1. Some statements represent marginal cases; that is, although they are not understood by the system, they are potentially comprehensible to it. These we can call actualizable problems. The development of the system is related precisely to these: if it draws on this potentiality of problem-solving which results in understanding such a statement, then its corpus of knowledge will be extended, while its level of knowledge, which separates the comprehensible from the incomprehensible, will be raised, and thereby newer problems will be brought into a position where they are potentially capable of being solved. The knowledge of a system concerning its universe appears in the form of statements formulated in a
STUDYING THE COGNITIVE AGENT: A Theory and Two Experiments
A cognitive theory is presented that accounts for a variety of cognitive behaviors as well as for certain noncognitive factors that are assumed to influence cognitive behavior. The theory is centered around the concept of cognitive agent and seeks to explain both its 'external' (observable) and 'internal' behavior. It is argued that psychological experimentation should be an integral part of the development of theory in cognitive science, in that such experimentation provides the only empirical basis available for choice of parameters for any computer model that implements such a theory. A psychological experiment is described which tested this assumption. A computer model, POPLAR, that implements the abstract theory and incorporates the data obtained as results of psychological experiment is described. Also further research plans are discussed.
Systems, Complex Systems, and Intelligence: an Educational Overview
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This contribution examines, for didactic purposes, the peculiarities of systems that have the ability to acquire, maintain and deactivate properties that cannot be deduced from those of their components. We evaluate complex systems that can acquire, lose, recover, vary the predominance of property sequences, characterized by their predominant coherence and variability, through the processes of self-organization and emergence, when coherence replaces organization. We consider correspondingly systemic epistemology as opposed to the classical analytic approach and to forms of reductionism. We outline aspects of the science of complexity such as coherence, incompleteness, quasiness and issues related to its modeling. We list and consider properties and types of complex systems. Then we are dealing with forms of correspondence that concern the original conception of intelligence of primitive artificial intelligence, which was substantially based on the high ability to manipulate symbols,...
Distributing cognition over humans and machines
1996
Abstract. This chapter considers computer-based learning environments from a sociocultural perspective. It relates several concepts from this approach with design principles and techniques specific to learning environments. We propose a metaphor intended to help designers of learning environments to make sense of system features within the socio-cultural perspective. This metaphor considers the software and the learner as a single cognitive system, variably distributed over a human and a machine. Keywords.
Cognitive Engineering: Toward a Workable Concept of Mind
Adaptive Perspectives on Human–Technology InteractionMethods and Models for Cognitive Engineering and Human-Computer Interaction, 2009
It seems plain to me now that the "cognitive revolution" ... was a response to the technological demands of the Post-Industrial Revolution. You cannot properly conceive of managing a complex world of information without a workable concept of mind.
2007
Complex Systems and the Cognitive Sciences: Potential for Pervasive Theoretical and Research Implications? Michael J. Jacobson (michael.jacobson@nie.edu.sg) Nanyang Technological University, Singapore Robert Goldstone (rgoldsto@indiana.edu) Indiana University Micki Chi (chi+@pitt.com) University of Pittsburgh Dor Abrahamson (dor@berkeley.edu) University of California, Berkeley Manu Kapur (manu.kapur@nie.edu.sg) Nanyang Technological University, Singapore William J. Clancey (William.J.Clancey@nasa.gov) NASA/Ames Research Center Keywords: Complex systems; knowledge representation; problem solving; ontologies; learning, agent-based modeling; scale free networks; alternative methodologies century. This presentation will: (a) argue for the importance of learning these ideas at the pre-college and college levels; (b) discuss research suggesting that there are significant cognitive challenges inherent in learning complex systems knowledge; and (c) consider ways that concepts and methodolog...