Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
In this paper we present Damon, a decentralized wide-area runtime aspect middleware built on top of a structured peer-topeer (p2p) substrate and a dynamic Aspect Oriented Programm...
Abstract. In previous work, we described a new approach to supporting userdefined type qualifiers, which augment existing types to specify and check additional properties of intere...
Brian Chin, Shane Markstrum, Todd D. Millstein, Je...
Abstract. Semantic Web Services were developed with the goal of automating the integration of business processes on the Web. The main idea is to express the functionality of the se...