Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
The Strength of Weak Learnability
Machine Learning
Letter Recognition Using Holland-Style Adaptive Classifiers
Machine Learning
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Generalizing from case studies: a case study
ML92 Proceedings of the ninth international workshop on Machine learning
Original Contribution: Stacked generalization
Neural Networks
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Machine Learning
Lazy Incremental Learning of Control Knowledge for EfficientlyObtaining Quality Plans
Artificial Intelligence Review - Special issue on lazy learning
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Using genetic programming to learn and improve control knowledge
Artificial Intelligence
A perspective view and survey of meta-learning
Artificial Intelligence Review
Evolving neural networks through augmenting topologies
Evolutionary Computation
Preventing "Overfitting" of Cross-Validation Data
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Proceedings of the 5th International Conference on Genetic Algorithms
Hyper-heuristics: Learning To Combine Simple Heuristics In Bin-packing Problems
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
A Hyperheuristic Approach to Scheduling a Sales Summit
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
Learning the Empirical Hardness of Optimization Problems: The Case of Combinatorial Auctions
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Evolving Heuristics for Planning
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
A Tabu-Search Hyperheuristic for Timetabling and Rostering
Journal of Heuristics
A Study on the use of "self-generation'' in memetic algorithms
Natural Computing: an international journal
Hyper-heuristics and classifier systems for solving 2D-regular cutting stock problems
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Learning to Solve Planning Problems Efficiently by Means of Genetic Programming
Evolutionary Computation
Dynamic Subset Selection Based on a Fitness Case Topology
Evolutionary Computation
Evolving Evolutionary Algorithms Using Linear Genetic Programming
Evolutionary Computation
Case-based heuristic selection for timetabling problems
Journal of Scheduling
A general heuristic for vehicle routing problems
Computers and Operations Research
Evolving evolutionary algorithms using evolutionary algorithms
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Computers and Industrial Engineering
Automated discovery of local search heuristics for satisfiability testing
Evolutionary Computation
A comprehensive analysis of hyper-heuristics
Intelligent Data Analysis
Enhanced generalized ant programming (EGAP)
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Avida-MDE: a digital evolution approach to generating models of adaptive software behavior
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Cross-disciplinary perspectives on meta-learning for algorithm selection
ACM Computing Surveys (CSUR)
Metalearning: Applications to Data Mining
Metalearning: Applications to Data Mining
GEVA: grammatical evolution in Java
ACM SIGEVOlution
Analyzing the landscape of a graph based hyper-heuristic for timetabling problems
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
GP-rush: using genetic programming to evolve solvers for the rush hour puzzle
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Evolutionary-based learning of generalised policies for AI planning domains
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Computational Statistics & Data Analysis
PDDL2.1: the art of the possible? commentary on fox and long
Journal of Artificial Intelligence Research
Adaptive problem-solving for large-scale scheduling problems: a case study
Journal of Artificial Intelligence Research
STRIPS: a new approach to the application of theorem proving to problem solving
IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
Dispatching rules for production scheduling: a hyper-heuristic landscape analysis
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
Automating the Design of Data Mining Algorithms: An Evolutionary Computation Approach
Automating the Design of Data Mining Algorithms: An Evolutionary Computation Approach
Learning action strategies for planning domains using genetic programming
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Theoretical results in genetic programming: the next ten years?
Genetic Programming and Evolvable Machines
Ant based hyper heuristic for physical impairment aware routing and wavelength assignment
Sarnoff'10 Proceedings of the 33rd IEEE conference on Sarnoff
Autonomous operator management for evolutionary algorithms
Journal of Heuristics
A scatter search based hyper-heuristic for sequencing a mixed-model assembly line
Journal of Heuristics
A genetic programming hyper-heuristic approach for evolving 2-D strip packing heuristics
IEEE Transactions on Evolutionary Computation
jGE: a Java implementation of grammatical evolution
ICS'06 Proceedings of the 10th WSEAS international conference on Systems
GA-FreeCell: evolving solvers for the game of FreeCell
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Building hyper-heuristics through ant colony optimization for the 2d bin packing problem
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Automating the packing heuristic design process with genetic programming
Evolutionary Computation
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Scaling Genetic Programming to Large Datasets Using Hierarchical Dynamic Subset Selection
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
HyFlex: a benchmark framework for cross-domain heuristic search
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
A hyper-heuristic evolutionary algorithm for automatically designing decision-tree algorithms
Proceedings of the 14th annual conference on Genetic and evolutionary computation
An Overview of Parameter Control Methods by Self-Adaptation in Evolutionary Algorithms
Fundamenta Informaticae
Adaptive evolutionary algorithms and extensions to the hyflex hyper-heuristic framework
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
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The fields of machine meta-learning and hyper-heuristic optimisation have developed mostly independently of each other, although evolutionary algorithms (particularly genetic programming) have recently played an important role in the development of both fields. Recent work in both fields shares a common goal, that of automating as much of the algorithm design process as possible. In this paper we first provide a historical perspective on automated algorithm design, and then we discuss similarities and differences between meta-learning in the field of supervised machine learning (classification) and hyper-heuristics in the field of optimisation. This discussion focuses on the dimensions of the problem space, the algorithm space and the performance measure, as well as clarifying important issues related to different levels of automation and generality in both fields. We also discuss important research directions, challenges and foundational issues in meta-learning and hyper-heuristic research. It is important to emphasize that this paper is not a survey, as several surveys on the areas of meta-learning and hyper-heuristics (separately) have been previously published. The main contribution of the paper is to contrast meta-learning and hyper-heuristics methods and concepts, in order to promote awareness and cross-fertilisation of ideas across the (by and large, non-overlapping) different communities of meta-learning and hyper-heuristic researchers. We hope that this cross-fertilisation of ideas can inspire interesting new research in both fields and in the new emerging research area which consists of integrating those fields.