Ofri Ziv

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We introduce a new class of multigrid temporal-difference learning algorithms for speeding up the estimation of the value function related to a stationary policy, within the context of discounted cost Markov decision processes with linear functional approximation. The proposed scheme builds on the multi-grid framework which is used in numerical analysis to(More)
Concurrency control poses significant challenges when composing computations over multiple data-structures (objects) with different concurrency-control implementations. We formalize the usually desired requirements (serializability, abort-safety, deadlock-safety, and opacity) as well as stronger versions of these properties that enable composition. We show(More)
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