In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...
Speed improvements in today's processors have largely been delivered in the form of multiple cores, increasing the importance of ions that ease parallel programming. Software...
Abstract. We study large-scale distributed cooperative systems that use optimistic replication. We represent a system as a graph of actions (operations) connected by edges that rei...
CSP was originally introduced as a parallel programming language in which sequential imperative processes execute concurrently and communicate by synchronized input and output. The...
A mobile robot acting in the world is faced with a large amount of sensory data and uncertainty in its action outcomes. Indeed, almost all interesting sequential decision-making d...