Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
This paper addresses the efficient processing of similarity queries in metric spaces, where data is horizontally distributed across a P2P network. The proposed approach does not r...
Abstract. Software agents are a promising technology for today's complex, distributed systems. Methodologies and techniques that address testing and reliability of multi agent...
Knowledge about user goals is crucial for realizing the vision of intelligent agents acting upon user intent on the web. In a departure from existing approaches, this paper propos...
Markus Strohmaier, Peter Prettenhofer, Mark Kr&oum...
Abstract-- We propose distributed algorithms to automatically deploy a group of robotic agents and provide coverage of a discretized environment represented by a graph. The classic...