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)

First paper introducing probabilisitic decision theory methods to AI problem solving.

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)

Adaptive Planning is an approach to planning in the commonsense domain. An adaptive planner takes advantage of the habitual nature of many of the planning situations for which it plans by bosing its activities on a memory of pre‐stored plans. A critical issue, and the subject of this paper, is the question of flexibility: How does an adaptive planner refit an old plan in order to meet the demands of some new planning situation? An adaptive planner refits prestored plans by (...) constructing an interpretation of the situation in which it is engaged. Key elements in the theory of adaptive planning are its treatment of specific plans and a notion of situation matching. The theory of adaptive planning has been modeled by a computer program called PLEXUS. (shrink)