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  1. Intelligence without representation.Rodney A. Brooks - 1991 - Artificial Intelligence 47 (1--3):139-159.
    Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity (...)
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  • Animate vision.Dana H. Ballard - 1991 - Artificial Intelligence 48 (1):57-86.
    Animate vision systems have gaze control mechanisms that can actively position the camera coordinate system in response to physical stimuli. Compared to passive systems, animate systems show that visual computation can be vastly less expensive when considered in the larger context of behavior. The most important visual behavior is the ability to control the direction of gaze. This allows the use of very low resolution imaging that has a high virtual resolution. Using such a system in a controlled way provides (...)
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  • Is complexity theory appropriate for analyzing biological systems?John K. Tsotsos - 1991 - Behavioral and Brain Sciences 14 (4):770-773.
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  • Analyzing vision at the complexity level.John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (3):423-445.
    The general problem of visual search can be shown to be computationally intractable in a formal, complexity-theoretic sense, yet visual search is extensively involved in everyday perception, and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The (...)
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  • A little complexity analysis goes a long way.John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (3):458-469.
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  • A complexity level analysis of vision.John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (3):423-445.
    The general problem of visual search can be shown to be computationally intractable in a formal, complexity-theoretic sense, yet visual search is extensively involved in everyday perception, and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The (...)
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  • Today the earwig, tomorrow man?David Kirsh - 1991 - Artificial Intelligence 47 (1-3):161-184.
    A startling amount of intelligent activity can be controlled without reasoning or thought. By tuning the perceptual system to task relevant properties a creature can cope with relatively sophisticated environments without concepts. There is a limit, however, to how far a creature without concepts can go. Rod Brooks, like many ecologically oriented scientists, argues that the vast majority of intelligent behaviour is concept-free. To evaluate this position I consider what special benefits accrue to concept-using creatures. Concepts are either necessary for (...)
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  • Visual search and stimulus similar¬ity.John Duncan & Glyn W. Humphreys - 1989 - Psychological Review 96 (3):433-458.
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  • New Approaches to Robotics.Rodney A. Brooks - unknown
    In order to build autonomous robots that can carry out useful work in unstructured environments new approaches have been developed to building intelligent systems. The relationship to traditional academic robotics and traditional artificial intelligence is examined. In the new approaches a tight coupling of sensing to action produces architectures for intelligence that are networks of simple computational elements which are quite broad, but not very deep. Recent work within this approach has demonstrated the use of representations, expectations, plans, goals, and (...)
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