Simulation-based optimization for material dispatching in a retailer network
WSC '04 Proceedings of the 36th conference on Winter simulation
Application of reinforcement learning to the game of Othello
Computers and Operations Research
Active audition using the parameter-less self-organising map
Autonomous Robots
Allocation of simulation runs for simulation optimization
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Optimizing time warp simulation with reinforcement learning techniques
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Resilient dynamic power management under uncertainty
Proceedings of the conference on Design, automation and test in Europe
Simulation-Based Optimization Approach for Software Cost Model with Rejuvenation
ATC '08 Proceedings of the 5th international conference on Autonomic and Trusted Computing
Experimental analysis of eligibility traces strategies in temporal difference learning
International Journal of Knowledge Engineering and Soft Data Paradigms
Simulation and reinforcement learning with soccer agents
Multiagent and Grid Systems - Innovations in intelligent agent technology
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Interfaces
Reinforcement Learning: A Tutorial Survey and Recent Advances
INFORMS Journal on Computing
Supervised Machine Learning: A Review of Classification Techniques
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Multi-objective evolutionary simulation-optimisation of a real-world manufacturing problem
Robotics and Computer-Integrated Manufacturing
Stopping small-sample stochastic approximation
ACC'09 Proceedings of the 2009 conference on American Control Conference
Hybrid design for multiple-goal task realization of robot arm with rotating table
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Supervised learning based power management for multicore processors
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
On-line adaptive algorithms in autonomic restart control
ATC'10 Proceedings of the 7th international conference on Autonomic and trusted computing
Uncertainty-aware dynamic power management in partially observable domains
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Reinforcement learning for model building and variance-penalized control
Winter Simulation Conference
Simulation optimization with hybrid golden region search
Winter Simulation Conference
Using genetic algorithms to limit the optimism in time warp
Winter Simulation Conference
Q-Learning and Enhanced Policy Iteration in Discounted Dynamic Programming
Mathematics of Operations Research
A modified particle swarm optimizer for engineering design
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Adaptive filter support selection for signal denoising based on the improved ICI rule
Digital Signal Processing
Real-world simulation-based manufacturing optimization using Cuckoo search
Proceedings of the Winter Simulation Conference
Scheduling fighter aircraft maintenance with reinforcement learning
Proceedings of the Winter Simulation Conference
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From the Publisher:"Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. Since it became possible to analyze random systems using computers, scientists and engineers have sought the means to optimize systems using simulation models. Only recently, however, has this objective had success in practice. Cutting-edge work in computational operations research, including non-linear programming (simultaneous perturbation), dynamic programming (reinforcement learning), and game theory (learning automata) has made it possible to use simulation in conjunction with optimization techniques. As a result, this research has given simulation added dimensions and power that it did not have in the recent past." "The book's objective is two-fold: (1) It examines the mathematical governing principles of simulation-based optimization, thereby providing the reader with the ability to model relevant real-life problems using these techniques. (2) It outlines the computational technology underlying these methods. Taken together, these two aspects demonstrate that the mathematical and computational methods discussed in this book do work." "Broadly speaking, the book has two parts: (1) parametric (static) optimization and (2) control (dynamic) optimization. Some of the book's special features are: an accessible introduction to reinforcement learning and parametric-optimization techniques; a step-by-step description of several algorithms of simulation-based optimization; a clear and simple introduction to the methodology of neural networks; a gentle introduction to convergence analysis of some of the methods enumerated above; and Computer programs for many algorithms of simulation-based optimization." This book is written for students and researchers in the fields of engineering (electrical, industrial and computer), computer science, operations research, management science, and applied mathematics.