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ATAL
2007
Springer
13 years 11 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
APPROX
2010
Springer
188views Algorithms» more  APPROX 2010»
13 years 6 months ago
Approximation Algorithms for Reliable Stochastic Combinatorial Optimization
We consider optimization problems that can be formulated as minimizing the cost of a feasible solution wT x over an arbitrary combinatorial feasible set F {0, 1}n . For these pro...
Evdokia Nikolova
RTAS
2008
IEEE
13 years 11 months ago
Bounding Worst-Case Response Time for Tasks with Non-Preemptive Regions
Real-time schedulability theory requires a priori knowledge of the worst-case execution time (WCET) of every task in the system. Fundamental to the calculation of WCET is a schedu...
Harini Ramaprasad, Frank Mueller