What Is Cognitive Science?
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Cognitive Science, as a discipline, is concerned with learning how animals (and machines) acquire knowledge, represent that knowledge, and how they manipulate those representations.
The study of Cognitive Science is fundamentally interdisciplinary. To understand functions of mind, scientists must increasingly apply the tools, methodology, and findings of one discipline to the problems of another. Cognitive psychologists, for example, must be familiar with computer science and artificial intelligence in order to design sophisticated models that emulate mental processes. Artificial intelligence researchers must understand advances in psychology, linguistics, and neuroscience in order to base their theories on psychologically and neurologically plausible foundations. Advances in such applied fields as robotics, computer speech recognition, and computer vision may stem from research on human
action and perception by researchers in psychology and linguistics. Work on machine learning can take advantage of what is known about human learning and development, as well as by studies of animal learning and cognition. Theories of problem solving and creative thinking can be informed by the work of philosophers of science who examine the course of conceptual change in science. Theories of human reasoning can make use of analyses of the formal structure of natural-language concepts by linguists and philosophers. Computer scientists and electrical engineers who are developing languages and architectures for spreading activation and distributed connectionist models of cognition must rely on analyses by mathematicians of the memory capacities and scale-up properties of these new models. Within the last decade, advances in the computational, behavioral, psychological, biological and neurological sciences have begun to bridge the historical gap that has existed between those exploring the physiology of the brain and those constructing symbolic computational models of the mind.
The advent of high performance workstations, advanced networking technologies and massively parallel supercomputers is making possible the establishment of environments for interdisciplinary cooperation that were heretofore unthinkable. Intelligent information processing in biological systems can in principle be emulated by machines, and in practice,
the construction of both hardware machines and software models that emulate aspects of thought, perception, learning, comprehension, coordination, vision and detailed brain function are bringing researchers together from previously isolated fields. Advances in
- theoretical foundations of knowledge and representation,
- experimentation in systems of natural and artificial intelligence, and
- technologies of computation and neuroscience
- Analytic: Perform logical analysis of functional constraints on cognition, of formal properties of systems for knowledge representation, as well as mathematical analysis of the time/space requirements for both natural and artificial systems, including scale-up ability of each model.
- Experimental: Design experiments to discriminate among rival theories of mental processing in natural and artificial intelligence systems. In natural systems, such experiments will be psychological or neurological in nature. Experimentation can also involve building and executing a computational model and then comparing its behavior against that predicted by theory and that found in nature.
- Synthetic: Construct artificial machines, in both software and hardware, capable of exhibiting various aspects of intelligent behavior.
All of the disciplines contributing to Cognitive Science share the overarching goal of developing formal theories of cognition. For psychologists, the goal of understanding the mind is expressed in terms of models of cognitive processes exhibited by humans and animals. For linguists, the goal is to gain theoretical understanding of the nature, acquisition, and use of human language. For neuroscientists, the goal is to understand how the organization and processing of massive ensembles of neural elements supports the emergence of high-level cognitive functions, and how lesions at the neural level manifest themselves in various cognitive deficits. For computer scientists and engineers, the goal is expressed in terms of the ultimate construction of robots capable of perception, coordinated motion, learning, language, and high-level reasoning. It is now abundantly clear that these goals are intimately intertwined.
In addition to seeking advances in formal theories of cognition, Cognitive Science is concerned with the exploitation of basic knowledge to achieve practical goals. Theoretical understanding of the mind and brain is already beginning to yield practical benefits in several realms. Information about how individuals reason and learn is being applied to improved teaching and testing methods, and to the design of intelligent tutoring systems. Research in artificial intelligence, robotics, and computer vision is helping to develop completely automated and cost-efficient manufacturing systems for industry. Medical diagnoses are aided by rule-based, expert-consultation systems, while advances in neural modeling are yielding insights into how damaged brains might be retrained. As it progresses in the 1990s and beyond, Cognitive Science promises to provide a multitude of practical benefits to society.
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