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 (...) additional constraints that dramatically simplify the computations of early vision. Another important behavior is the way the environment “behaves‘. Animate systems under real-time constraints can further reduce their computational burden by using environmental cues that are perspicuous in the local context. A third source of economy is introduced when behaviors are learned. Because errors are rarely fatal, systems using learning algorithms can amortize computational cost over extended periods. Further economies can be achieved when the learning system uses indexical reference, which is a form of dynamic variable binding. Animate vision is a natural way of implementing this dynamic binding. (shrink)

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 (...) producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments. (shrink)

Connectionism and classicism, it generally appears, have at least this much in common: both place some notion of internal representation at the heart of a scientific study of mind. In recent years, however, a much more radical view has gained increasing popularity. This view calls into question the commitment to internal representation itself. More strikingly still, this new wave of anti-representationalism is rooted not in armchair theorizing but in practical attempts to model and understand intelligent, adaptive behavior. In this paper (...) we first present, and then critically assess, a variety of recent anti-representationalist treatments. We suggest that so far, at least, the sceptical rhetoric outpaces both evidence and argument. Some probable causes of this premature scepticism are isolated. Nonetheless, the anti-representationalist challenge is shown to be both important and progressive insofar as it forces us to see beyond the bare representational/non-representational dichotomy and to recognize instead a rich continuum of degrees and types of representationality. (shrink)

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 (...) certain types of perception, learning, and control, or they make those processes computationally simpler. Once a creature has concepts its capacities are vastly multiplied. (shrink)

Bringing about desirable collisions (making interceptions) and avoiding unwanted collisions are critically important sensorimotor skills, which appear to require us to estimate the time remaining before collision occurs (time-to-collision). Until recently the theoretical approach to understanding time-to-collision estimation has been dominated by the tau-hypothesis, which has its origins in J.J. Gibson’s ecological approach to perception. The hypothesis proposes that a quantity (tau), present in the visual stimulus, provides the necessary time-to-collision information. Empirical results and formal analyses have now accumulated to (...) demonstrate conclusively that the tau-hypothesis is false. This article describes an alternative approach that is based on recent data showing that the information used in judging time-to-collision is task- and situation-dependent, is of many different origins (of which tau is just one) and is influenced by the information-processing constraints of the nervous system. (shrink)

Anydomainofscientificresearchhasitssustainingorthodoxy. Thatis, research on a problem, whether in astronomy, physics, or biology, is con- ducted against a backdrop of broadly shared assumptions. It is these as- sumptionsthatguideinquiryandprovidethecanonofwhatisreasonable-- of what "makes sense." And it is these shared assumptions that constitute a framework for the interpretation of research results. Research on the problem of how we see is likewise sustained by broadly shared assump- tions, where the current orthodoxy embraces the very general idea that the business of the visual system is to (...) create a detailed replica of the visual world, and that it accomplishes its business via hierarchical organization and by operatingessentiallyindependently of other sensorymodalitiesas well as independently of previous learning, goals, motor planning, and motor execution. (shrink)

To describe phenomena that occur at different time scales, computational models of the brain must incorporate different levels of abstraction. At time scales of approximately 1/3 of a second, orienting movements of the body play a crucial role in cognition and form a useful computational level embodiment level,” the constraints of the physical system determine the nature of cognitive operations. The key synergy is that at time scales of about 1/3 of a second, the natural sequentiality of body movements can (...) be matched to the natural computational economies of sequential decision systems through a system of implicit reference called deictic in which pointing movements are used to bind objects in the world to cognitive programs. This target article focuses on how deictic bindings make it possible to perform natural tasks. Deictic computation provides a mechanism for representing the essential features that link external sensory data with internal cognitive programs and motor actions. One of the central features of cognition, working memory, can be related to moment-by-moment dispositions of body features such as eye movements and hand movements. (shrink)

--œWhere Brain, Body, and World Collide--� reprinted by permission of Daedalus, Journal of the American Academy of Arts and Sciences, from the issue entitled, --œThe Brain,--� Spring 1998, Vol. 127, No. 2.

Much work in economics, the social sciences, and elsewhere takes as it starting oint a somewhat unrealistic conception of rationality- a conception that ignores or downplays both the temporal and the situated aspects of human reason. Biological reason, I shall argue, is better concieved as an iterated process of adaptive response made under extreme time pressure and exquisitely keyed to a variety of external structures and circumstances.

Recent studies such as Thelen and Smith, Kelso, Van Gelder, Beer, and others have presented a forceful case for a dynamical systems approach to understanding cognition and adaptive behavior. These studies call into question some foundational assumptions concerning the nature of cognitive scientific explanation and the role of notions such as internal representation and computation. These are exciting and important challenges. But they must be handled with care. It is all to easy in this debate to lose sight of the (...) explanatorily important issues and to talk at cross purposes, courtesy of the various ways in which different theorists often concieve key terms. (shrink)