Much Learning is done by way of studying precedents and exercises. A teacher supplies a story, gives a problem, and expects a student both to solve a problem and to discover a principle. The student must find the correspondence between…

his dissertation analyzes how local knowledge improves environmental decisions. The premise is that controlling pollution and addressing public health disparities are not problems that professionals alone can solve. Concerned lay publics, especially low-income populations and people of color that experience…

by Robert W. Sommer., Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1992., Title as it appears in the M.I.T. Graduate List, June 1992: Building internal knowledge networks in multinational corporations, a study of cross-border research and development., Includes…

Software authors: Webster P. Dove and Cory Meyers ; Document author: Evangelos E. Milios., "October 1984.", Includes bibliographical references (p. 63) and index., Supported by Advanced Research Projects Agency, monitored by ONR. N00014-81-K-0742 NR-049-506. Supported by Sanders Associates, and an…

by Vignir Mar Haraldsson., Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Political Science, 2000., Includes bibliographical references (leaves 54-56).

There are many situations in which a very detailed low-level description encodes, through a hierarchical organization, a recognizable higher-order pattern. The macro-molecular structural conformations of proteins exhibit higher order regularities whose recognition is complicated by many factors. ARIADNE searches for…

The next generation of artificial intelligence programs will require the ability to organize knowledge as groups of active objects. Each object should have only its own local expertise, the ability to operate in parallel with other objects, and the ability…

As advances in computer architecture and changing economics make feasible machines with large-scale parallelism, Artificial Intelligence will require new ways of thinking about computation that can exploit parallelism effectively. We present the actor model of computation as being appropriate for…

This paper presents a novel algorithm for learning in a class of stochastic Markov decision processes (MDPs) with continuous state and action spaces that trades speed for accuracy. A transform of the stochastic MDP into a deterministic one is presented…

We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this paper we show that regularization networks encompass a much…