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Learning to optimize via posterior sampling
Russo, Daniel; Van Roy, Benjamin - In: Mathematics of operations research 39 (2014) 4, pp. 1221-1243
Persistent link: https://www.econbiz.de/10010462145
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Efficient reinforcement learning in deterministic systems with value function generalization
Wen, Zheng; Van Roy, Benjamin - In: Mathematics of operations research 42 (2017) 3, pp. 762-782
Persistent link: https://www.econbiz.de/10011742485
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Satisficing in time-sensitive bandit learning
Russo, Daniel; Van Roy, Benjamin - In: Mathematics of operations research 47 (2022) 4, pp. 2815-2839
Persistent link: https://www.econbiz.de/10014311390
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A Cost-Shaping Linear Program for Average-Cost Approximate Dynamic Programming with Performance Guarantees
de Farias, Daniela Pucci; Van Roy, Benjamin - In: Mathematics of operations research 31 (2006) 3, pp. 597-620
Persistent link: https://www.econbiz.de/10007282670
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Performance Loss Bounds for Approximate Value Iteration with State Aggregation
Van Roy, Benjamin - In: Mathematics of operations research 31 (2006) 2, pp. 234-244
Persistent link: https://www.econbiz.de/10007282693
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On Constraint Sampling in the Linear Programming Approach to Approximate Dynamic Programming
de Farias, Daniela Pucci; Roy, Benjamin Van - In: Mathematics of operations research 29 (2004) 3, pp. 462-478
Persistent link: https://www.econbiz.de/10006417600