Realization of an Adaptive Memetic Algorithm Using Differential Evolution and Q-Learning: A Case Study in Multirobot Path Planning
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Pratyusha Rakshit | Amit Konar | Lakhmi C. Jain | Swagatam Das | Atulya K. Nagar | Pavel Bhowmik | Indrani Goswami | L. Jain | Swagatam Das | A. Nagar | A. Konar | Indranil Goswami | P. Bhowmik | P. Rakshit
[1] David B. Fogel,et al. A Note on the Empirical Evaluation of Intermediate Recombination , 1995, Evolutionary Computation.
[2] P. Cowling,et al. CHOICE FUNCTION AND RANDOM HYPERHEURISTICS , 2002 .
[3] Andries Petrus Engelbrecht,et al. Differential evolution methods for unsupervised image classification , 2005, 2005 IEEE Congress on Evolutionary Computation.
[4] Amit Konar,et al. Distributed cooperative multi-robot path planning using differential evolution , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).
[5] Carlos A. Coello Coello,et al. A comparative study of differential evolution variants for global optimization , 2006, GECCO.
[6] William A. Gruver,et al. Motion planning with time-varying polyhedral obstacles based on graph search and mathematical programming , 1990, Proceedings., IEEE International Conference on Robotics and Automation.
[7] Joachim Coche. An evolutionary approach to the examination of capital market efficiency , 1998 .
[8] R. W. Derksen,et al. Differential Evolution in Aerodynamic Optimization , 1999 .
[9] H. Le-Huy,et al. Robot path planning using neural networks and fuzzy logic , 1994, Proceedings of IECON'94 - 20th Annual Conference of IEEE Industrial Electronics.
[10] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[11] Tucker R. Balch,et al. Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..
[12] S.X. Yang,et al. A Knowledge Based GA for Path Planning of Multiple Mobile Robots in Dynamic Environments , 2006, 2006 IEEE Conference on Robotics, Automation and Mechatronics.
[13] Ivan Zelinka,et al. ON STAGNATION OF THE DIFFERENTIAL EVOLUTION ALGORITHM , 2000 .
[14] Meryem Simsek,et al. Improved decentralized Q-learning algorithm for interference reduction in LTE-femtocells , 2011, 2011 Wireless Advanced.
[15] Stan C. A. M. Gielen,et al. Neural Network Dynamics for Path Planning and Obstacle Avoidance , 1995, Neural Networks.
[16] Iraj Hassanzadeh,et al. Path planning for a mobile robot using fuzzy logic controller tuned by GA , 2009, 2009 6th International Symposium on Mechatronics and its Applications.
[17] Chris Watkins,et al. Learning from delayed rewards , 1989 .
[18] Madhu Sudan,et al. Motion planning on a graph , 1994, Proceedings 35th Annual Symposium on Foundations of Computer Science.
[19] Ming C. Lin,et al. Constraint-Based Motion Planning Using Voronoi Diagrams , 2002, WAFR.
[20] Peter Dayan,et al. Q-learning , 1992, Machine Learning.
[21] Zbigniew Michalewicz,et al. Adaptive evolutionary planner/navigator for mobile robots , 1997, IEEE Trans. Evol. Comput..
[22] Lynne E. Parker,et al. Path Planning and Motion Coordination in Multiple Mobile Robot Teams , 2009 .
[23] R. Storn,et al. Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .
[24] Jing J. Liang,et al. Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .
[25] Graham Kendall,et al. A Hyperheuristic Approach to Scheduling a Sales Summit , 2000, PATAT.
[26] Takanori Shibata,et al. Intelligent motion planning by genetic algorithm with fuzzy critic , 1993, Proceedings of 8th IEEE International Symposium on Intelligent Control.
[27] Majid Nili Ahmadabadi,et al. Interaction of Culture-based Learning and Cooperative Co-evolution and its Application to Automatic Behavior-based System Design , 2010, IEEE Transactions on Evolutionary Computation.
[28] Yusuke Aoki,et al. GA-Based Q-Learning to Develop Compact Control Table for Multiple Agents , 2010 .
[29] Lakhmi C. Jain,et al. Intelligent Autonomous Systems: Foundations and Applications , 2010, Intelligent Autonomous Systems.
[30] Punit Pandey,et al. Approximate Q-Learning: An Introduction , 2010, 2010 Second International Conference on Machine Learning and Computing.
[31] Chien-Chou Lin,et al. Motion Planning Using a Memetic Evolution Algorithm for Swarm Robots , 2012 .
[32] K. K. Bharadwaj,et al. An Efficient Global Optimization Approach to Multi Robot Path Exploration Problem Using Hybrid Genetic Algorithm , 2008, 2008 4th International Conference on Information and Automation for Sustainability.
[33] Tadahiko Murata,et al. Multi-Legged Robot Control Using GA-Based Q-Learning Method With Neighboring Crossover , 2008 .
[34] Xin Ma,et al. Genetic Algorithm-based Multi-robot Cooperative Exploration , 2007, 2007 IEEE International Conference on Control and Automation.
[35] Wei Liu,et al. Enhanced Q-learning algorithm for dynamic power management with performance constraint , 2010, 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010).
[36] Yew-Soon Ong,et al. Memetic Computation—Past, Present & Future [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.
[37] Amit Konar,et al. Differential Evolution with Local Neighborhood , 2006, 2006 IEEE International Conference on Evolutionary Computation.
[38] Zbigniew Michalewicz,et al. Intelligent Decision Support: A Fuzzy Stock Ranking System , 2009, Aspects of Natural Language Processing.
[39] Qin Zhang,et al. Immunity-Based Adaptive Genetic Algorithm for Multi-robot Cooperative Exploration , 2007, ICIC.
[40] Pratyusha Rakshit,et al. Multi-robot path-planning using artificial bee colony optimization algorithm , 2011, 2011 Third World Congress on Nature and Biologically Inspired Computing.
[41] Amit Konar,et al. Differential Evolution Using a Neighborhood-Based Mutation Operator , 2009, IEEE Transactions on Evolutionary Computation.
[42] R. Lewontin. ‘The Selfish Gene’ , 1977, Nature.
[43] K. K. Bharadwaj,et al. A Hybrid Evolutionary Approach for Multi Robot Path Exploration Problem , 2008 .
[44] Amit Konar,et al. Cooperative multi-robot path planning using differential evolution , 2009, J. Intell. Fuzzy Syst..
[45] Saku Kukkonen,et al. Real-parameter optimization with differential evolution , 2005, 2005 IEEE Congress on Evolutionary Computation.
[46] Swagatam Das,et al. Automatic Clustering Using an Improved Differential Evolution Algorithm , 2007 .
[47] SRIDHAR MAHADEVAN,et al. Average Reward Reinforcement Learning: Foundations, Algorithms, and Empirical Results , 2005, Machine Learning.
[48] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[49] Kostas E. Bekris,et al. Efficient and complete centralized multi-robot path planning , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[50] Thomas Dean,et al. Reinforcement Learning for Planning and Control , 1993 .
[51] Indrani Goswami,et al. Conditional Q-learning algorithm for path-planning of a mobile robot , 2010, 2010 International Conference on Industrial Electronics, Control and Robotics.
[52] Kevin Kok Wai Wong,et al. Classification of adaptive memetic algorithms: a comparative study , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[53] Jing J. Liang,et al. Novel composition test functions for numerical global optimization , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..
[54] Kenneth V. Price,et al. An introduction to differential evolution , 1999 .
[55] Yiming Yang,et al. Applying Q-Learning Algorithm to Study Line-Grasping Control Policy for Transmission Line Deicing Robot , 2010, 2010 International Conference on Intelligent System Design and Engineering Application.
[56] Lihong Li,et al. PAC model-free reinforcement learning , 2006, ICML.
[57] Janez Brest,et al. Performance comparison of self-adaptive and adaptive differential evolution algorithms , 2007, Soft Comput..
[58] Uday K. Chakraborty,et al. Advances in Differential Evolution , 2010 .
[59] Dinesh Manocha,et al. Multi-robot coordination using generalized social potential fields , 2009, 2009 IEEE International Conference on Robotics and Automation.
[60] P. N. Suganthan,et al. Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization , 2009, IEEE Transactions on Evolutionary Computation.
[61] Marina L. Gavrilova,et al. Roadmap-Based Path Planning - Using the Voronoi Diagram for a Clearance-Based Shortest Path , 2008, IEEE Robotics & Automation Magazine.
[62] E. Ebrahimi,et al. Self-adaptive memetic algorithm: an adaptive conjugate gradient approach , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..
[63] Zhen Ji,et al. Memetic Ant Colony Optimization for Band Selection of Hyperspectral Imagery Classification , 2010, 2010 Chinese Conference on Pattern Recognition (CCPR).
[64] Amit Konar,et al. Two-Dimensional IIR Filter Design with Modern Search Heuristics: a Comparative Study , 2006, Int. J. Comput. Intell. Appl..
[65] Dinko Osmankovic,et al. Implementation of Q — Learning algorithm for solving maze problem , 2011, 2011 Proceedings of the 34th International Convention MIPRO.
[66] Hitoshi Iba,et al. A study on the computational efficiency of Baldwinian evolution , 2010, 2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC).
[67] Peter J. Angeline,et al. Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences , 1998, Evolutionary Programming.
[68] A. Kai Qin,et al. Self-adaptive differential evolution algorithm for numerical optimization , 2005, 2005 IEEE Congress on Evolutionary Computation.