Abstract. Wireless sensor networks come of age and start moving out of the laboratory into the field. As the number of deployments is increasing the need for an efficient and relia...
We develop a behavioural theory of distributed programs in the presence of failures such as nodes crashing and links breaking. The framework we use is that of D, a language in whi...
Abstract—This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discu...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Abstract. We propose the study of graphs that are defined by lowcomplexity distributed and deterministic agents. We suggest that this viewpoint may help introduce the element of in...