This paper analyzes the suitability of reinforcement learning (RL) for both programming and adapting situated agents. We discuss two RL algorithms: Q-learning and the Bucket Brigade. We introduce a special case of the Bucket Brigade, and analyze and compare its…

We develop a novel autonomous control synthesis strategy called Phase Space Navigator for the automatic synthesis of nonlinear control systems. The Phase Space Navigator generates global control laws by synthesizing flow shapes of dynamical systems and planning and navigating system…

We develop a qualitative method for understanding and representing phase space structures of complex systems and demonstrate the method with a program, MAPS --- Modeler and Analyzer for Phase Spaces, using deep domain knowledge of dynamical system theory. Given a…

A key problem in model-based object recognition is selection, namely, the problem of determining which regions in the image are likely to come from a single object. In this paper we present an approach that extracts and uses color region…

If we are to understand the innately human ability to solve complex problems, we must first understand the cognitive processes that allow us to combine different kinds of knowledge, to learn new things and to communicate with other people. I…

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There is a great need among educators for a way to quickly assign teams in large or distance learning classrooms in a manner superior to random assignment or student self-selection. Forming teams based on knowledge of students' characteristics is too…

Build is a tool for keeping modular systems in a consistent state by managing the construction tasks (e.g. compilation, linking, etc.) associated with such systems. It employs a user supplied system model and a procedural description of a task to…

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