Showing papers by "Nils J. Nilsson published in 1968"

A Formal Basis for the Heuristic Determination of Minimum Cost Paths

Abstract: Although the problem of determining the minimum cost path through a graph arises naturally in a number of interesting applications, there has been no underlying theory to guide the development of efficient search procedures. Moreover, there is no adequate conceptual framework within which the various ad hoc search strategies proposed to date can be compared. This paper describes how heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching and demonstrates an optimality property of a class of search strategies.

Searching problem-solving and game-playing trees for minimal cost solutions.

Abstract: A wheel for rolling stock such as a tractor which comprises a wheel rim carrying a pneumatic tire having an annular tire cavity and a plurality of substantially spherical balls having a relatively high density, a packed layer of the ball partly filling the tire cavity. When the axis of the wheel is positioned horizontally, the wheel can have a gravity center at a lower point than the axis thereof due to the presence of the heavy balls positioned at the bottom portion of the tire cavity.

Some Ideas on Information Processing in the Cerebellum

Abstract: Other papers presented at this conference tend to deal either with extremely formalised models of neural networks, or with peripheral processing. Therefore, it may be a useful reminder of how much further such studies have to go if we present here some ideas on information processing in the cerebellum, to emphasize how complicated real neuronic interactions can be, and to emphasize how ignorant we are of “the language of neurons” when we move away from the periphery. Here we attempt to formulate questions rather than provide answers — our hope being that we may remind the theorist of a vast range of exacting problems, and stimulate the biologist to learn new types of experimental questions. Our models are not yet in predictive form, not least because much crucial experimental data is lacking — we hope that experimentalists, reading between the lines, will be prompted to carry out new experiments, and then confront the theorists with the task of appropriately refining our approach. We clearly have a long way to go before we can be satisfied with any models of complex neural structures which are not located in the mainstream of the input and output systems.