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Topic: Fitness landscapes

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	Fitness landscape - Wikipedia, the free encyclopedia
		In evolutionary biology, fitness landscapes or adaptive landscapes are used to visualize the relationship between genotypes (or phenotypes) and replicatory success.
		This fitness is the "height" of the landscape.
		Fitness landscapes are often conceived of as ranges of mountains.
	en.wikipedia.org /wiki/Fitness_landscape (635 words)

	Fitness Landscapes (Site not responding. Last check: 2007-11-07)
		Fitness landscapes are a valuable concept in evolutionary biology, combinatorial optimization, and the physics of disordered systems.
		A fitness landscape is a mapping from a configuration space that is equipped with some notion of adjacency, nearness, distance or accessibility, into the real numbers.
		Landscape theory has emerged as an attempt to devise suitable mathematical structures for describing the ``static'' properties of landscapes as well as their influence on the dynamics of adaptation.
	www.tbi.univie.ac.at /papers/Abstracts/01-pfs-004abs.html (90 words)

	Fitness Landscapes Arising from the Sequence-Structure Maps (Site not responding. Last check: 2007-11-07)
		Fitness landscapes are an important concept in molecular evolution since evolutionary adaptation as well as in vitro selection of biomolecules can be viewed as a hill-climbing-like process.
		Biologically relevant landscape models are based on the assumption that genotypes give rise to phenotypes that are evaluated by their environment and hence determine the genotype's fitness.
		While rugged landscapes without neutral neighbors lead to localized populations, trapping in local optima, and the existence of a critical replication rate beyond which sequence information is lost, we find diffusion in sequence space and ever-lasting innovation of novel mutants on landscapes arising from RNA or protein folding.
	www.tbi.univie.ac.at /papers/Abstracts/97-09-001abs.html (230 words)

	Chapter 3: ADAPTABILITY
		The optimum position on any landscape would be defined as the highest "peak" and the least attractive position would be considered the lowest "valley".
		What's interesting about this landscape is that, even though it's obvious that we are either climbing or descending, we cannot tell whether we are climbing towards one of the optimum peaks on the landscape, or one of the lowest peaks.
		Namely, as we explore the surrounding landscape, we assess our fitness level at each point and either adapt our capacities to increase fitness at that point, or move in a direction in which our existing capacities would be more effective.
	co-i-l.com /coil/knowledge-garden/oi/books/odp/chapter3/fitness.shtml (1994 words)

	A Study of Arithmetic Genetic Encoding for Highly Randomized Fitness Landscapes (Site not responding. Last check: 2007-11-07)
		In particular, we will consider a computational problem typical of the highly random landscapes that the genetic algorithms are usually subjected to, and discuss some of the problems that such an endeavour might meet with.
		As the fitness calculation is expensive, the life of a single run will be assumed to be the life of the strategy being evaluated.
		Coevolving a transfer function from the genetic string to the actual parameters would be like "shaping up" the fitness landscape for optimum performance of the GA. A problem to tackle would be whether this could be done in an exclusive encoding.
	personal.vsnl.com /udayan/age1.htm (1103 words)

	Fitness Landscapes
		In many cases, the rather abstract and mathematically complex structure of a system of attractors and basins can be replaced by the more intuitive model of a fitness landscape.
		The fitness function transforms the state space into a fitness landscape, where every point in the space has a certain "height" corresponding to its fitness value.
		Thus, A has a higher fitness (or lower potential) than B. The bottoms of the valleys A, B and C are local minima of the potential, i.e.
	pespmc1.vub.ac.be /FITLANDS.html (399 words)

	Extrema Selection: Accelerated Evolution on Neutral Networks (Site not responding. Last check: 2007-11-07)
		This assumption is that fitness landscapes are made up of peaks and valleys, and in order to get from one peak to another peak, one must travel through a valley.
		Generally, fitness is both how good a solution the particular individual is to the problem at hand, as well as a measure of its relative likelihood of producing genetically related offspring.
		In order to determine the improvement on the different landscapes, each method of evolution (extrema selection and normal selection) was run for 10000 individuals, and the improvement was taken to be the difference in the fitness between the best individuals found.
	chat.carleton.ca /~tcstewar/papers/extrema.html (3484 words)

	[No title]
		Whilst the metaphor of Ôfitness landscapesÕ is widely applied in the evolutionary algorithm (EA) community, there are several assumptions requiring its application that are often ignored, such as the underlying structure of the search space and the ontological status of the values depicted by the landscape.
		The height of the surface at a particular point represented either the fitness of the individual specified by that point, or the mean fitness of the population.
		It is not surprising, therefore, that the idea of a fixed Ôfitness landscapeÕ has come to represent objective values or evaluations, not least since this surface may be constructed over the whole of the genotypic space.
	technology.open.ac.uk /tel/people/hirst/tony/pub/doc/AISB97landscapes.doc (6455 words)

	Canonical Approximation of Fitness Landscapes - Happel, Stadler (ResearchIndex) (Site not responding. Last check: 2007-11-07)
		Abstract: We present a method for approximating a fitness landscape as a superposition of "elementary" landscapes.
		Given a correlation function of the landscape in question we show that the relative amplitudes of contributions with p-ary interactions can be computed.
		Fitness Landscapes Since Sewall Wright's seminal paper [1] the notion of a fitness landscape underlying the dynamics of evolutionary optimization has proved to be one of the most...
	citeseer.ist.psu.edu /9887.html (837 words)

	Chapter 3: ADAPTABILITY
		If the landscape was comprised of many low peaks of uniform height and many solutions were equally acceptable, this system would operate effectively and ignore any challenges made to the whole system or any disturbance in the environment.
		This approach to organization is optimised by having a balance between the varied input of various landscapes, exploration of the space of possibility, and continual improvement on whatever peak is currently being climbed.
		We live in a world of interconnected landscapes, or spaces of possibility, that are always changing due to the action of others, like ourselves, attempting to climb various peaks, or explore and exploit the same spaces of possibility.
	www.co-i-l.com /coil/knowledge-garden/oi/books/odp/chapter3/chapter3.shtml (7486 words)

	McKinsey Quarterly: Escaping the Red Queen effect (Site not responding. Last check: 2007-11-07)
		Evolution is sometimes characterized by biologists as a metaphorical uphill struggle across a “fitness landscape” in which mountain peaks represent high “fitness,” or ability to survive, and valleys represent low fitness.
		Since N is 4, this fitness landscape can be mapped in a four-dimensional space, where each of the possible peptides is at one of the 16 corners of a four-dimensional cube, or hypercube.
		K thus reflects the degree to which the nodes on the landscape are interconnected in determining the overall fitness of the landscape.
	gemini.tntech.edu /~mwmcrae/esre95.html (4055 words)

	[No title]
		Fit and Functional Effectiveness “Whether I’m talking about peptides or chairs, I need a notion of the fit and the functional effectiveness of the entity,” Kauffman explained.
		Once the fitness of each chair option was established, Kauffman took us on an “adaptive walk.” The term aptly describes the process complexity scientists use to evaluate the fitness of alternative options—in this case, chair comfort—on a fitness landscape.
		Landscapes aren’t random.” In At Home in the Universe, he writes: “No complex entity that has evolved has done so on a random fitness landscape.
	www.snhu.edu /img/assets/3655/Adaptation_and_Coevolution_on_an_Emergent_Global_Competitive_Landscape.doc (1834 words)

	Understanding Competitive Co-evolutionary Dynamics via Fitness Landscapes ...
		In this paper we focus on a particular form of competitive co-evolutionary EA and study the dynamics of the fitness of the best individuals in the evolving populations.
		Our approach is to try to understand the characteristics of the fitness landscapes that produce particular kinds of fitness dynamics such as stable fixed points, stable cycles, and instability.
		These landscapes are extremely similar when inspected with respect to traditional properties such as ruggedness/modality, yet they yield very different results.
	www.cs.bham.ac.uk /~wbl/biblio/gecco2004/prof219.html (135 words)

	Brainstorms: IC, CSI, and fitness landscape topology
		One landscape consists of sparse needle-like columns jutting out of an endless death valley; another is made up of smoothly rising ridges and ranges.
		The expression "fitness landscape" when applied to biological evolution tends to conflate physical terra firma with abstract mathematical topology, with the effect of making the latter seem as obvious and convincing as walking up a hill.
		We could construct a fitness landscape for this problem by making the lower 900 bits a (very large) number representing an x-axis coordinate, the upper 900 bits the y-axis, and some relative measure of tone discrimination the z-axis, such that z = f(x, y), the fitness function.
	www.iscid.org /boards/ubb-get_topic-f-6-t-000038.html (2685 words)

	Neutrality in Fitness Landscapes - Reidys, Stadler (SMEALSearch) - Pal,Rangaswamy,Giles,Debnath (Site not responding. Last check: 2007-11-07)
		While various measures of ruggedness (correlation functions, adaptive walks, or the density of local optima) are reasonably well understood, and models for constructing landscapes with a desired degree of ruggedness are readily available, very little is known about neutrality.
		We introduce the notion of additive random landscapes as a framework for tuning both neutrality and ruggedness at once, and we develop a formalism that allows the explicit computation of the most salient parameters that are associated with neutrality in landscapes of this type.
		7 Correlation structure of the landscape of the graph-bipartit..
	gunther.smeal.psu.edu /reidys99neutrality.html (1021 words)

	Untitled Document
		Therefore, a change in overall fitness by one species on its landscape may deform the peaks on the landscape of a different species.
		However, the fitness landscapes of the mice and the lions are coupled together.
		An improvement in fitness for one patch may mean a degradation in fitness for the system as a whole.
	www.mgtaylor.com /mgtaylor/jotm/summer97/complexity3.htm (3387 words)

	ALIFE VI abstract: Ruggedness and Neutrality - the NKp Family of Fitness Landscapes (Site not responding. Last check: 2007-11-07)
		It has come to be almost an article of faith amongst population biologists and GA researchers alike that the principal feature of a fitness landscape as regards evolutionary dynamics is "ruggedness", particularly as measured by the auto-correlation function.
		We introduce the NKp family of landscapes (a variant on NK landscapes) which possess the remarkable property that varying the degree of neutrality has minimal effect on the correlation structure.
		It is demonstrated that NKp landscapes feature neutral networks which have a "constant innovation" property comparable with the neutral networks observed in models of RNA secondary structure folding landscapes.
	alife6.alife.org /abstracts/RU76.html (211 words)

	Byrne & Rogers: Link 10 (Site not responding. Last check: 2007-11-07)
		The idea of 'fitness landscapes' is central to this paper and requires development.
		Biologists have long harbored images of fitness landscapes, where the peaks represent high fitness, and populations wander under the drives of mutation, selection and random drift across the landscape seeking peaks, but perhaps never achieving them.
		The idea of fitness landscape is an image of the contemporary state of a co-evolutionary system.
	www.socresonline.org.uk /1/2/link10.html (373 words)

	[No title] (Site not responding. Last check: 2007-11-07)
		In dynamic landscapes, however, the use of the ?bestso-farÄ values are inappropriate, because the values are meaningless after a landscape change.
		Collective fitness is defined as the average best-of-generation values, averaged over a sufficient number of generations, G?, required to expose the EA to a representative sample of all possible landscape dynamics, further averaged over multiple runs.
		Use of this method ensures that experimental results are based on a representative sample of the landscape dynamics and provides a basis for determination of the statistical significance of observed experimental results in dynamic fitness landscapes.
	www.ubka.uni-karlsruhe.de /vvv/2003/wiwi/1/1.text (2369 words)

	[No title]
		Organizational decision-making Hill-climbing search of the fitness landscape would be an appropriate model of managerial decision-making if all N decisions were made by a single, boundedly rational executive devoted to maximization of fitness.
		In landscape models, it is common to think of firms or other searching entities as getting stuck on local peaks and only on such peaks; that is, the sets of sticking points and local peaks are identical.
		On the fitness landscape shown in Table 1, the choice configuration 1111 is a local peak for the firm.
	emertech.wharton.upenn.edu /Working_Papers/OrgStickingPts1.0.doc (6094 words)

	CEC99 SPECIAL SESSIONS (Site not responding. Last check: 2007-11-07)
		Characterization of trajectory structure of fitness landscapes is a major problem of EC theory.
		This discrepancy can be traced to the different ways that the concept of fitness appears -- as a measure of the number of fit offspring, or as a measure of the probability to reach reproductive age.
		Effective fitness models the former not the latter and gives an intuitive way to understand population dynamics as flows on an effective fitness landscape when genetic operators other than selection play an important role.
	garage.cps.msu.edu /cec99/specialSessions/Fogel.html (1699 words)

	LoBue: Enterprise Evolution: Terms: Fitness Landscapes
		An agent may have traits with a high fitness function in one environment and thus be likely to be "selected" for (which means it lives long enough to reproduce).
		On the other hand, having a low fitness function in an environment means the agent is less likely to be "selected" and thus to die without reproducing.
		A low level of fitness will mean the company may fail (i.e., go extinct) while a high level of fitness should mean the company will prosper—unless the business environment changes in such a way that the company no longer has a high fitness function.
	www.lobue.com /enterprise_evolution/knowledge_fitland.html (324 words)

	Fitness landscapes and adaptation (Site not responding. Last check: 2007-11-07)
		is the average fitness of the allele calculated as the weighted average fitness over all genotypes in which the allele occurs.
		Fitness surface (below), in the absence of linkage disequilibrium, is a smooth hill with a single peak.
		Once a population enters the influence of a large fitness peak, mass selection drives the population toward the fitness maximum.
	www.wsu.edu /~mmorgan/biol519f01/node31.html (888 words)

	Evolutionary and Adaptive Systems (EASy) at Sussex (Site not responding. Last check: 2007-11-07)
		It should be noted that from a fitness landscape perspective much of this type of work deals essentially with "needle in a haystack" models.
		Many striking results are derived analytically, such as expected average fitness, fitness fluctuations, population distributions, expected duration of epochs, etc. The techniques employed are very powerful and would seem to be applicable to more general scenarios.
		Peliti, L. Fitness landscapes and evolution Lectures given at the NATO ASI on Physics of Biomaterials: Fluctuations, Self-Organization and Evolution, Geilo, Norway, March 27, April 6, 1995.
	www.cogs.susx.ac.uk /easy/ResearchSeminars/NeutralNetworks_Bibliography.html (2376 words)

	Knowledge-at-work: Knowledge landscapes
		Landscapes with their fitness gradients, their species niches and evolutionary selection, give a whole new meaning to the term knowledge ecology - memes & genes - will talk about this another time.
		Knowledge landscapes apply to individuals, groups and organizations, there are the same fractal qualities we observe when moving up-scale from sand grains to rocks to mountains, the same linkages, relationships, competitive games, sources and sinks that characterize personal KM, CoPs and organizational learning.
		Often times it seems to me, our fitness landscape is not only complex, but heaving at the same time in the knowledge world!.
	denham.typepad.com /km/2003/10/knowledge_lands.html (405 words)

	Fractal Geometry (Site not responding. Last check: 2007-11-07)
		where d(x,y) is the genetic distance between the strings x and y, f(x) is the fitness of the string x, and E is the expected value.
		If the current string length happens to be much shorter than the maximum length, then the landscape can appear to be fractal.
		Experiments with populations of random sequences trying to reach a particular target configuration typically exhibit long periods of stasis, characterized by an approximately Gaussian random walk, punctuated by intermittent adaptations, Levy flights.
	classes.yale.edu /fractals/CA/FractalFitness/FractalFitness.html (176 words)

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