This paper considers the self-stabilizing unison problem. The contribution of this paper is threefold. First, we establish that when any self-stabilizing asynchronous unison protoc...
Christian Boulinier, Franck Petit, Vincent Villain
This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state spac...
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Many important applications, such as those using sparse data structures, have memory reference patterns that are unknown at compile-time. Prior work has developed runtime reorderi...
Michelle Mills Strout, Larry Carter, Jeanne Ferran...