Shaping can be an effective method for improving the learning rate in reinforcement systems. Previously, shaping has been heuristically motivated and implemented. We provide a for...
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
In this paper we describe Maestro, a dataflow computation framework for Ibis, our Java-based grid middleware. The novelty of Maestro is that it is a self-organizing peer-to-peer s...
—In open multiagent systems, agents need to model their environments in order to identify trustworthy agents. Models of the environment should be accurate so that decisions about...
—Large scale production grids are a major case for autonomic computing. Following the classical definition of Kephart, an autonomic computing system should optimize its own beha...