Elements of information theory
Elements of information theory
A fast quantum mechanical algorithm for database search
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Digital evolution in time-dependent fitness landscapes
Artificial Life
Genetic Algorithms Reference
On the futility of blind search: An algorithmic view of “no free lunch”
Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Remarks on a recent paper on the "no free lunch" theorems
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Entropy-Boltzmann selection in the genetic algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An Effective PSO-Based Memetic Algorithm for Flow Shop Scheduling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust stability analysis of discrete-time systems using genetic algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Adaptive learning of hypergame situations using a genetic algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Volterra-system identification using adaptive real-coded genetic algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Solving the Identifying Code Problem by a Genetic Algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Robot Path Integration in Manufacturing Processes: Genetic Algorithm Versus Ant Colony Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Method of Inequality-Based Multiobjective Genetic Algorithm for Domestic Daily Aircraft Routing
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Interactive Particle Swarm: A Pareto-Adaptive Metaheuristic to Multiobjective Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
OPSO: Orthogonal Particle Swarm Optimization and Its Application to Task Assignment Problems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Bernoulli's principle of insufficient reason and conservation of information in computer search
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Evolutionary synthesis of nand logic: dissecting a digital organism
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms
Information Sciences: an International Journal
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Conservation of information theorems indicate that any search algorithm performs, on average, as well as random search without replacement unless it takes advantage of problem-specific information about the search target or the search-space structure. Combinatorics shows that even a moderately sized search requires problem-specific information to be successful. Computers, despite their speed in performing queries, are completely inadequate for resolving even moderately sized search problems without accurate information to guide them. We propose three measures to characterize the information required for successful search: 1) endogenous information, which measures the difficulty of finding a target using random search; 2) exogenous information, which measures the difficulty that remains in finding a target once a search takes advantage of problem-specific information; and 3) active information, which, as the difference between endogenous and exogenous information, measures the contribution of problem-specific information for successfully finding a target. This paper develops a methodology based on these information measures to gauge the effectiveness with which problem-specific information facilitates successful search. It then applies this methodology to various search tools widely used in evolutionary search.