We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy but may behave differently due to position-dependent inputs. All...
: This chapter presents the problematic of the distributed systems supervision through a comprehensive state-of-the-art. Issues are illustrated with a case study about an innovativ...
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
We present an iterative, reading-based methodology for analyzing defects in source code when change history is available. Our bottom-up approach can be applied to build knowledge ...
Multithreading has been proposed as an architectural strategy for tolerating latency in multiprocessors and, through limited empirical studies, shown to offer promise. This paper ...
Rafael H. Saavedra-Barrera, David E. Culler, Thors...