Adaptive Online Time Allocation to Search Algorithms
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Jürgen Schmidhuber | Matteo Gagliolo | Viktor Zhumatiy | J. Schmidhuber | Viktor Zhumatiy | M. Gagliolo
[1] John R. Rice,et al. The Algorithm Selection Problem , 1976, Adv. Comput..
[2] Stuart J. Russell,et al. Principles of Metareasoning , 1989, Artif. Intell..
[3] Eric Horvitz,et al. Computational tradeoffs under bounded resources , 2001, Artif. Intell..
[4] Ivana Kruijff-Korbayová,et al. A Portfolio Approach to Algorithm Selection , 2003, IJCAI.
[5] F. Lobo,et al. A parameter-less genetic , 1999 .
[6] Michail G. Lagoudakis,et al. Reinforcement Learning for Algorithm Selection , 2000, AAAI/IAAI.
[7] Johannes Fürnkranz,et al. On the Use of Fast Subsampling Estimates for Algorithm Recommendation , 2002 .
[8] Nichael Lynn Cramer,et al. A Representation for the Adaptive Generation of Simple Sequential Programs , 1985, ICGA.
[9] Thomas Stützle,et al. A Racing Algorithm for Configuring Metaheuristics , 2002, GECCO.
[10] Bart Selman,et al. Algorithm portfolios , 2001, Artif. Intell..
[11] Mark S. Boddy,et al. Deliberation Scheduling for Problem Solving in Time-Constrained Environments , 1994, Artif. Intell..
[12] Everette S. Gardner,et al. Exponential smoothing: The state of the art , 1985 .
[13] Hans-Paul Schwefel,et al. Parallel Problem Solving from Nature — PPSN IV , 1996, Lecture Notes in Computer Science.
[14] Michail G. Lagoudakis,et al. Algorithm Selection using Reinforcement Learning , 2000, ICML.
[15] Oren Etzioni,et al. Embedding Decision-Analytic Control in a Learning Architecture , 1991, Artif. Intell..
[16] Shlomo Zilberstein,et al. Monitoring and control of anytime algorithms: A dynamic programming approach , 2001, Artif. Intell..
[17] Yoav Shoham,et al. A portfolio approach to algorithm select , 2003, IJCAI 2003.
[18] Marek Petrik,et al. Statistically Optimal Combination of Algorithms , 2004 .
[19] João Gama,et al. On Data and Algorithms: Understanding Inductive Performance , 2004, Machine Learning.
[20] Carlos Soares,et al. A Meta-Learning Method to Select the Kernel Width in Support Vector Regression , 2004, Machine Learning.
[21] Thomas Stützle,et al. SATLIB: An Online Resource for Research on SAT , 2000 .
[22] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[23] Bernd Freisleben,et al. New Genetic Local Search Operators for the Traveling Salesman Problem , 1996, PPSN.
[24] R. Solomonoff. Progress In Incremental Machine Learning , 2003 .
[25] Shlomo Zilberstein,et al. Anytime Sensing Planning and Action: A Practical Model for Robot Control , 1993, IJCAI.
[26] Ricardo Vilalta,et al. Introduction to the Special Issue on Meta-Learning , 2004, Machine Learning.
[27] Booncharoen Sirinaovakul,et al. Introduction to the Special Issue , 2002, Comput. Intell..
[28] Jürgen Schmidhuber,et al. Optimal Ordered Problem Solver , 2002, Machine Learning.
[29] Hilan Bensusan,et al. Meta-Learning by Landmarking Various Learning Algorithms , 2000, ICML.
[30] David Maxwell Chickering,et al. A Bayesian Approach to Tackling Hard Computational Problems (Preliminary Report) , 2001, Electron. Notes Discret. Math..
[31] Andrew W. Moore,et al. Efficient Algorithms for Minimizing Cross Validation Error , 1994, ICML.
[32] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[33] Corso Elvezia. Probabilistic Incremental Program Evolution , 1997 .