778 research outputs found

    Simple Random Sampling Estimation of the Number of Local Optima

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    MOST Space Telescope Photometry of the 2010 January Transit of Extrasolar Planet HD80606b

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    We present observations of the full January 2010 transit of HD80606b from the Canadian microsatellite, Microvariability and Oscillations of Stars (MOST). By employing a space-based telescope, we monitor the entire transit thus limiting systematic errors that result from ground observations. We determine measurements for the planetary radius (R_{p}=0.987\pm0.061R_{Jup}) and inclination (i=89.283^{o}\pm0.024) by constraining our fits with the observed parameters of different groups. Our measured mid-transit time of 2455210.6449\pm0.0034 HJD is consistant with the 2010 Spitzer results and is 20 minutes earlier than predicted by groups who observed the June 2009 transit.Comment: 3 figure

    How fast does the stationary distribution of the Markov chain modelling EAs concentrate on the homogeneous populations for small mutation rate?

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    The state space of the Markov chain modelling an evolutionary algorithm is quite large especially if the population space and the search space are large. I shell introduce an appropriate notion of "coarse graining" for such Markov chains. Indeed, from the mathematical point of view, this can be called a quotient of a Markov chain by an equivalence relation over the state space. The newly obtained Markov chain has a significantly smaller state space and it\u27s stationary distribution is "coherent" with the initial large chain. Although the transition probabilities of the coarse-grained Markov chain are defined in terms of the stationary distribution of the original big chain, in some cases it is possible to deduce interesting information about the stationary distribution of the original chain in terms of the quatient chain. I will demonstrate how this method works. I shell also present some simple results and open questions

    On the Effects of Incorporating Memory in GC-AIS for the Set Cover Problem

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    Learning is an important part of the immune system by which the immune system maintains a memory of the infections it has encountered to protect against future attacks. In this paper we incorporate the mechanism of maintaining a memory in the recently proposed GC-AIS algorithm. GC-AIS has shown good performance on the static set cover problem (SCP) in recent work [13] and we are interested in investigating the merits of GC-AIS in a dynamic setting. We compare the affect of GC-AIS with and without a memory approach on the dynamic SCP instances, which are created with varying degrees of modifications to instances from [2]. Three types of modifications are proposed in the paper by adding, removing or editing the subsets from the original problem instances. It is shown that for the case of adding subsets to the original instance using our memory approach is always beneficial while for the case of removing subsets using our memory approach almost always results in worse performance than when not utilising memory. Finally in the cases with editing subsets it is shown that for lower levels of modification using our memory approach gives better results while when the level of modification is higher our memory based approach is worse than using no memory.authorsversio

    Linear multi-objective drift analysis

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    Organisation-Oriented Coarse Graining and Refinement of Stochastic Reaction Networks

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    The authors acknowledge support from the European Union through funding under FP7–ICT–2011–8 project HIERATIC 14 (316705). We also thank the anonymous reviewers for their helpful and detailed comments.Peer reviewedPostprin

    Reinterpreting No Free Lunch

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    Since it’s inception, the “No Free Lunch theorem” has concerned the application of symmetry results rather than the symmetries themselves. In our view, the conflation of result and application obscures the simplicity, generality, and power of the symmetries involved. This paper separates result from application, focusing on and clarifying the nature of underlying symmetries. The result is a general set-theoretic version of NFL which speaks to symmetries when arbitrary domains and co-domains are involved. Although our framework is deterministic, we note situations where our deterministic set-theoretic results speak nevertheless to stochastic algorithms

    Group Properties of Crossover and Mutation

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    It is supposed that the finite search space Ω has certain symmetries that can be described in terms of a group of permutations acting upon it. If crossover and mutation respect these symmetries, then these operators can be described in terms of a mixing matrix and a group of permutation matrices. Conditions under which certain subsets of Ω are invariant under crossover are investigated, leading to a generalization of the term schema. Finally, it is sometimes possible for the group acting on Ω to induce a group structure on Ω itself
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