We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents, and present a framework that uses this paradigm t...
The web log data embed much of web users' browsing behavior. From the web logs, one can discover patterns that predict the users' future requests based on their current b...
The original design of the Internet and its underlying protocols did not anticipate users to be mobile. With the growing interest in supporting mobile users and mobile computing, ...
This paper studies the problem of modeling complex domains of actions and change within highlevel action description languages. We investigate two main issues of concern: (a) can ...
A large body of research in machine learning is concerned with supervised learning from examples. The examples are typically represented as vectors in a multi-dimensional feature ...