— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
Reasoning about agents that we observe in the world is challenging. Our available information is often limited to observations of the agent’s external behavior in the past and p...
H. Van Dyke Parunak, Sven Brueckner, Robert S. Mat...
Web services send and receive messages in XML syntax with some parts hashed, encrypted or signed, according to the WS-Security standard. In this paper we introduce a model to forma...
— Today’s system monitoring tools are capable of detecting system failures such as host failures, OS errors, and network partitions in near-real time. Unfortunately, the same c...
Dan Gunter, Brian Tierney, Aaron Brown, D. Martin ...
This paper defines a new, context-driven programming model for pervasive spaces. Existing models are prone to conflict, as it is hard to predict the outcome of interleaved actions ...