by Kah-Peng Aw., Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management, 2001., Includes bibliographical references (leaf 55).

by Christopher Granger Atkeson., Thesis (Ph. D.)--Massachusetts Institute of Technology, Whitaker College of Health Sciences, Technology, and Management, Dept. of Brain and Cognitive Sciences, 1986., MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE, Bibliography: leaves 143-154.

This paper describes ARLO, a representation language loosely modelled after Greiner and Lenant's RLL-1. ARLO is a structure-based representation language for describing structure-based representation languages, including itself. A given representation language is specified in ARLO by a collection of structures…

This paper presents an adaptive learning model for market-making under the reinforcement learning framework. Reinforcement learning is a learning technique in which agents aim to maximize the long-term accumulated rewards. No knowledge of the market environment, such as the order…

Many systems have been developed for constructing decision trees from collections of examples. Although the decision trees generated by these methods are accurate and efficient, they often suffer the disadvantage of excessive complexity that can render them incomprehensible to experts.…

This thesis considers three complications that arise from applying reinforcement learning to a real-world application. In the process of using reinforcement learning to build an adaptive electronic market-maker, we find the sparsity of data, the partial observability of the domain,…

Humans recognize optical reflectance properties of surfaces such as metal, plastic, or paper from a single image without knowledge of illumination. We develop a machine vision system to perform similar recognition tasks automatically. Reflectance estimation under unknown, arbitrary illumination proves…

We have developed a technique called RISE (Random Image Structure Evolution), by which one may systematically sample continuous paths in a high-dimensional image space. A basic RISE sequence depicts the evolution of an object's image from a random field, along…

Consider a world of 'objects.' Our goal is to place these objects into categories that are useful to the observer using sensory data. One criterion for utility is that the categories allow the observer to infer the object's potential behaviors,…

Explanation-based Generalization requires that the learner obtain an explanation of why a precedent exemplifies a concept. It is, therefore, useless if the system fails to find this explanation. However, it is not necessary to give up and resort to purely…