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An Evolution Strategy with Coordinate System Invariant Adaptation of Arbitrary Normal Mutation Distributions Within the Concept of Mutative Strategy Parameter Control
 PROCEEDINGS OF THE GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, GECCO99
, 1999
"... A selfadaptation of arbitrary normal mutation distributions within the concept of mutative strategy parameter control (MSC) using a newly formulated mutation operator is introduced. The coordinate system independent formulation ensures the invariance of the algorithm towards arbitrary linear ..."
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Cited by 5 (1 self)
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A selfadaptation of arbitrary normal mutation distributions within the concept of mutative strategy parameter control (MSC) using a newly formulated mutation operator is introduced. The coordinate system independent formulation ensures the invariance of the algorithm towards arbitrary linear
Completely Derandomized SelfAdaptation in Evolution Strategies
 Evolutionary Computation
, 2001
"... This paper puts forward two useful methods for selfadaptation of the mutation distribution  the concepts of derandomization and cumulation. Principle shortcomings of the concept of mutative strategy parameter control and two levels of derandomization are reviewed. Basic demands on the selfadapta ..."
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Cited by 549 (58 self)
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This paper puts forward two useful methods for selfadaptation of the mutation distribution  the concepts of derandomization and cumulation. Principle shortcomings of the concept of mutative strategy parameter control and two levels of derandomization are reviewed. Basic demands on the self
Active Perception
, 1988
"... Active Perception (Active Vision specifically) is defined as a study of Modeling and Control strategies for perception. By modeling we mean models of sensors, processing modules and their interaction. We distinguish local models from global models by their extent of application in space and time. T ..."
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Cited by 431 (12 self)
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. The local models represent procedures and parameters such as optical distortions of the lens, focal lens, spatial resolution, bandpass filter, etc. The global models on the other hand characterize the overall performance and make predictions on how the individual modules interact. The control strategies
Approximate accelerated stochastic simulation of chemically reacting systems
 J. Chem. Phys
, 2001
"... The stochastic simulation algorithm ͑SSA͒ is an essentially exact procedure for numerically simulating the time evolution of a wellstirred chemically reacting system. Despite recent major improvements in the efficiency of the SSA, its drawback remains the great amount of computer time that is ofte ..."
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Cited by 346 (6 self)
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that is often required to simulate a desired amount of system time. Presented here is the ''leap'' method, an approximate procedure that in some circumstances can produce significant gains in simulation speed with acceptable losses in accuracy. Some primitive strategies for control
A Survey of Evolution Strategies
 Proceedings of the Fourth International Conference on Genetic Algorithms
, 1991
"... Similar to Genetic Algorithms, Evolution Strategies (ESs) are algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems. The development of Evolution Strategies from the first mutationselection scheme to the refined (¯,)ES including the gen ..."
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Cited by 263 (3 self)
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Similar to Genetic Algorithms, Evolution Strategies (ESs) are algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems. The development of Evolution Strategies from the first mutationselection scheme to the refined (¯,)ES including
On the Adaptation of Arbitrary Normal Mutation Distributions in Evolution Strategies: The Generating Set Adaptation
, 1995
"... A new adaptation scheme for adapting arbitrary normal mutation distributions in evolution strategies is introduced. It can adapt correct scaling and correlations between object parameters. Furthermore, it is independent of any rotation of the objective function and reliably adapts mutation dis ..."
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Cited by 227 (31 self)
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A new adaptation scheme for adapting arbitrary normal mutation distributions in evolution strategies is introduced. It can adapt correct scaling and correlations between object parameters. Furthermore, it is independent of any rotation of the objective function and reliably adapts mutation
Experienceweighted Attraction Learning in Normal Form Games
 ECONOMETRICA
, 1999
"... We describe a general model, `experienceweighted attraction' (EWA) learning, which includes reinforcement learning and a class of weighted fictitious play belief models as special cases. In EWA, strategies have attractions which reflect prior predispositions, are updated based on payoff experi ..."
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Cited by 279 (27 self)
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. When delta = 1, levels of reinforcement of strategies are proportional to expected payoffs given beliefs based on past history. Another key feature is the growth rates of attractions. The EWA model controls the growth rates by two decay parameters, phi and rho, which depreciate attractions and amount
Selforganizing hierarchical particle swarm optimizer with timevarying acceleration coefficients
 IEEE Transactions on Evolutionary Computation
, 2004
"... Abstract—This paper introduces a novel parameter automation strategy for the particle swarm algorithm and two further extensions to improve its performance after a predefined number of generations. Initially, to efficiently control the local search and convergence to the global optimum solution, tim ..."
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Cited by 194 (2 self)
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Abstract—This paper introduces a novel parameter automation strategy for the particle swarm algorithm and two further extensions to improve its performance after a predefined number of generations. Initially, to efficiently control the local search and convergence to the global optimum solution
Introducing the Tileworld: Experimentally evaluating agent architectures
 In Proceedings of the National Conference on Artificial Intelligence
, 1990
"... We describe a system called Tileworld, which consists of a simulated robot agent and a simulated environment which is both dynamic and unpredictable. Both the agent and the environment are highly parameterized, enabling one to control certain characteristics of each. We can thus experimentally inves ..."
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Cited by 195 (13 self)
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investigate the behavior of various metalevel reasoning strategies by tuning the parameters of the agent, and can assess the success of alternative strategies in dierent environments by tuning the environmental parameters. Our hypothesis is that the appropriateness of a particular metalevel reasoning
General AIMD Congestion Control
, 2000
"... Instead of the increasebyone decreasetohalf strategy used in TCP Reno for congestion window adjustment, we consider the general case such that the increase value and decrease ratio are parameters. That is, in the congestion avoidance state, the window size is increased by ff per window of pac ..."
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Cited by 144 (6 self)
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Instead of the increasebyone decreasetohalf strategy used in TCP Reno for congestion window adjustment, we consider the general case such that the increase value and decrease ratio are parameters. That is, in the congestion avoidance state, the window size is increased by ff per window
Results 1  10
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4,442