We consider the policy search approach to reinforcement learning. We show that if a “baseline distribution” is given (indicating roughly how often we expect a good policy to v...
J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng, Jeff...
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Software process improvement (SPI) has emerged as a critical area for organizations involved in software development. There is now considerable evidence that SPI can provide subst...
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
: Student modeling approaches predominantly focus on modeling student knowledge. For effective learning, however, it is necessary to teach students how to learn, as well as to prov...