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» Iterative Learning Control - Monotonicity and Optimization
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GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
15 years 3 months ago
Expensive optimization, uncertain environment: an EA-based solution
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Maumita Bhattacharya
JDCTA
2010
272views more  JDCTA 2010»
14 years 4 months ago
Optimal Control of Nonlinear Systems Using the Homotopy Perturbation Method: Infinite Horizon Case
This paper presents a new method for solving a class of infinite horizon nonlinear optimal control problems. In this method, first the original optimal control problem is transfor...
Amin Jajarmi, Hamidreza Ramezanpour, Arman Sargolz...
CDC
2008
IEEE
108views Control Systems» more  CDC 2008»
15 years 4 months ago
On the state-space design of optimal controllers for distributed systems with finite communication speed
— We consider the problem of designing optimal distributed controllers whose impulse response has limited propagation speed. We introduce a state-space framework in which such co...
Makan Fardad, Mihailo R. Jovanovic
ICML
2010
IEEE
14 years 10 months ago
Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis
We introduce new, efficient algorithms for value iteration with multiple reward functions and continuous state. We also give an algorithm for finding the set of all nondominated a...
Daniel J. Lizotte, Michael H. Bowling, Susan A. Mu...
ISCA
2008
IEEE
137views Hardware» more  ISCA 2008»
15 years 4 months ago
Self-Optimizing Memory Controllers: A Reinforcement Learning Approach
Efficiently utilizing off-chip DRAM bandwidth is a critical issue in designing cost-effective, high-performance chip multiprocessors (CMPs). Conventional memory controllers deli...
Engin Ipek, Onur Mutlu, José F. Martí...