Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...
t) Peter W. O’Hearn Queen Mary, University of London In the 1960s Dijkstra suggested that, in order to limit the complexity of potential process interactions, concurrent programs...
This paper investigates reinforcement learning (RL) in XCS. First, it formally shows that XCS implements a method of generalized RL based on linear approximators, in which the usu...
We introduce constraint differentiation, a powerful technique for reducing search when model-checking security protocols using constraint-based methods. Constraint differentiation...
We present a proof calculus and method for the static verification of assertions and procedure specifications in shared-memory concurrent programs. The key idea in our approach is...