We describe an application of inductive logic programming to transfer learning. Transfer learning is the use of knowledge learned in a source task to improve learning in a related ...
Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richa...
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
As our business, academic, and personal lives continue to move at an ever-faster pace, finding times for busy people to meet has become an art. One of the most perplexing challeng...
Mike Brzozowski, Kendra Carattini, Scott R. Klemme...
We describe a formal framework for diagnosis and repair problems that shares elements of the well known partially observable MDP and cost-sensitive classification models. Our cost...
Michael L. Littman, Nishkam Ravi, Eitan Fenson, Ri...
Database system architectures are undergoing revolutionary changes. Most importantly, algorithms and data are being unified by integrating programming languages with the database ...