bluuebunny/crossref_metadata_2025 huggingface dataset:
Hydrodynamic Factors in Dandy-Walker and Arnold-Chiari Malformations
Authors: Gardner James
Published: February 2008

The Dandy-Walker malformation (DWM) is hydrocephalus that primarily affects the fourth ventricle, whose overdistention involves also the aqueduct and third ventricle. However, just the opposite is true in the Arnold-Chiari malformation (ACM) since the hydrocephalus is limited to the lateral ventricles which squeeze the third ventricle between them and compress the aqueduct and fourth ventricle. The evidence indicates that both result from hydrodynamic stresses in embryonal and early fetal life. This communication is offered in rebuttal to some statements in an otherwise authoritative and comprehensive article.
Organizing Hematoma in a Child Presenting as a ‘Doughnut Lesion’ on Nuclear Scan
Authors: Harris Vivian J. , Meeks Wrophas , Goldbarg Hilda
Published: February 2008

We report a 4½-year-old boy who presented with a 4-week history of frontal headaches and fever, and generalized convulsion 5 months previously. Papilledema, an abnormal EEG and a brain scan with a frontal mass and ‘doughnut’ sign were found. The association of the clinical history with brain scan findings strongly suggested a brain abscess. At surgery the lesion proved to be an encapsulated hematoma; Histological findings suggest underlying microangiomata.
Congenital Anomaly of the Odontoid in Children
Authors: Davis Dudley , Gutierrez Francisco A.
Published: February 2008

The embryologic origins of congenital abnormalities of the odontoid process are reviewed. Four cases of odontoid dysgenesis in childhood are presented. All of our cases were associated with a head injury, which subsequently led to the diagnosis. Pain was the most common presenting complaint in our patients. Decreased cervical mobility was the most consistent physical finding. There was no major neurological defect implicating spinal cord compression in any of our patients. This is not true of adults with congenital abnormalities of the odontoid, particularly those with atlantoaxial instability. The diagnosis of odontoid dysgenesis is a radiographic one. Flexion-extension films, tomograms and cineradiograms are often required to make the diagnosis. C1–C2 subluxation, either anterior or posterior is often found. Prompt posterior cervical fusion is recommended as the treatment of choice.
Dissemination with Malignant Changes from a Pineal Tumor through the Corpus callosum after Total Removal
Authors: Carrillo Raffael , Ricoy José R. , del Pozo José M. , García-Uria José , Herrero José
Published: February 2008

Within the germinal neoplasms of the central nervous system, the embryonal carcinoma is a very rare tumor. The authors report such a lesion arising on the corpus callosum in a child 8 months after a differentiated teratoma was totaly removed from the pineal region. The classification of the germ cell tumors of the central nervous system and their relation with similar tumors of the gonads are discussed. The treatment of the pineal tumors is also discussed.
Cerebral Angiography and Evaluation of Functional Status of Shunts in Hydrocephalic Children
Authors: Carrillo Rafael
Published: February 2008

It is generally possible to evaluate a malfunctioning shunt on the basis of clinical signs. Neuroradiologic evaluation is recommended for the difficult cases when this is not possible. The neuroradiologic procedure of choice is cerebral angiography since it permits the determination of ventricular size, an estimate of the presence of intraventricular hypertension, and an evaluation of the nature and degree of brain shift or herniation. Furthermore, such complications of hydrocephalus as porencephaly or subdural accumulations of fluid may also be diagnosed.
Neurological Complications of Osteopetrosis
Authors: Amacher Loren
Published: February 2008

Twin girls with the congenital form of osteopetrosis have been followed for 4 years. Their clinical course provides a compendium of the neurological complications of this disorder.
Displacement of the Superior Sagittal Sinus Associated with a Brain Tumor
Authors: Zilkha Albert , Wiltshire Hugo E. , Irwin Gerald A.L. , Borofsky Leatrice G.
Published: February 2008

A 13-year-old girl with an 11½-year history of seizures, was found to have a brain tumor and contralateral displacement of the superior sagittal sinus and falx. The rarity and possible mechanisms of sagittal sinus displacement are discussed.
The Study of Cerebrospinal Fluid Dynamics in Apparently ‘Arrested’ Hydrocephalus in Children
Authors: Di Rocco Concezio , Caldarelli Massimo , Maira Giulio , Rossi Gian Franco
Published: February 2008

18 children having hydrocephalus, which could be regarded clinically as ‘arrested’, underwent cerebral angiography and a constant infusion manometric test. Intracranial pressure was directly recorded in 3 cases. The above examinations indicated that hydrocephalus was still ‘active’ in 8 children. This was confirmed by the good results of the surgical treatment.
Accumulation of Zinc in Human Atherosclerotic Lesions Correlates With Calcium Levels But Does Not Protect Against Protein Oxidation
Authors: Stadler Nadina , Stanley Naomi , Heeneman Sylvia , Vacata Vladimir , Daemen Mat J.A.P. , Bannon Paul G. , Waltenberger Johannes , Davies Michael J.
Published: February 2008

Objective—

Oxidized lipids and proteins, as well as decreased antioxidant levels, have been detected in human atherosclerotic lesions, with oxidation catalyzed by iron and copper postulated to contribute to lesion development. Zinc has been postulated to displace iron from critical sites and thereby protect against damage. In this study, metal ion and protein oxidation levels were quantified in human carotid and abdominal artery specimens containing early-to-advanced lesions, to determine whether zinc concentrations correlate inversely with iron levels and protein oxidation.

Methods and Results—

Metal ions were quantified by EPR and inductively coupled plasma mass spectroscopy. Native and oxidized protein side-chains were quantified by high-performance liquid chromatography. Elevated levels of zinc (≈6-fold) were detected in advanced lesions compared to healthy tissue or early lesions. Zinc did not correlate negatively with iron or copper levels suggesting that zinc does not displace these metal ions. Highly significant positive correlations (
P
<0.005) were detected between zinc and calcium levels.

Conclusions—

Zinc did not correlate with low iron levels and reduced protein oxidation. These data indicate that zinc does not prevent protein oxidation in advanced lesions. The reported protective effect of zinc accumulation is proposed to be associated with lesion calcification.
Homocysteine Inhibits Arterial Endothelial Cell Growth Through Transcriptional Downregulation of Fibroblast Growth Factor-2 Involving G Protein and DNA Methylation
Authors: Chang Po-Yuan , Lu Shao-Chun , Lee Chii-Ming , Chen Yi-Jie , Dugan Tracey A. , Huang Wen-Huei , Chang Shwu-Fen , Liao Warren S.L. , Chen Chu-Huang , Lee Yuan-Teh
Published: February 2008

Homocysteine (Hcy) contributes to atherogenesis and angiostasis by altering the phenotype of arterial endothelial cells (ECs). The present study was aimed at elucidating potential mechanisms by which Hcy can slow EC proliferation and induce EC apoptosis, thereby disrupting endothelial integrity. Given the strong mitogenic and antiapoptotic properties of fibroblast growth factor (FGF)2, we examined whether Hcy can modulate its expression. In cultured human coronary and bovine aortic ECs, Hcy exerted time- and concentration-dependent (0 to 500 μmol/L) reduction of the mRNA and protein levels of FGF2, whereas vascular endothelial growth factor expression was not affected until Hcy reached a proapoptotic 500 μmol/L. By testing a panel of signal transduction inhibitors, we found that the Hcy-induced downregulation of FGF2 was specifically attenuated by pertussis toxin, an inhibitor of Gi protein signaling. Hcy induced cell cycle arrest at the G
1
/S transition and increased TUNEL-positive apoptotic cells in a graded manner. These effects were effectively counteracted by exogenous FGF2. Reporter gene assays showed that Hcy downregulated FGF2 by transcriptional repression of the gene promoter encompassed in a CpG dinucleotide-rich island. This region was heavily methylated at the cytosine residues by Hcy despite decreased methylation potential (
S
-adenosylmethionine to
S
-adenosylhomocysteine ratio). Normal levels of FGF2 transcription were restored to ECs simultaneously exposed to Hcy and 5-aza-deoxycytidine. We conclude that homocysteine disrupts the growth and survival of ECs through a G protein–mediated pathway associated with altered promoter DNA methylation and the transcriptional repression of FGF2.
Early Seizures in Cerebral Vein and Dural Sinus Thrombosis
Authors: Ferro José M. , Canhão Patrícia , Bousser Marie-Germaine , Stam Jan , Barinagarrementeria Fernando
Published: February 2008

Backgound and Purpose—

The risk of seizure early after the diagnosis of cerebral vein and dural sinus thrombosis (CVT) is not known, and the use of prophylactic antiepileptic (AED) medication in the acute phase of CVT is controversial.

Methods—

In a multicenter, prospective, observational study, we analyzed the risk factors for seizures experienced before the diagnosis of CVT was confirmed (presenting seizures) or within the following 2 weeks (early seizures). The risk of occurrence of early seizures was compared in 4 risk strata and related to whether patients received AEDs or not. Criteria for the strata were “presenting seizures” and “supratentorial lesions.”

Results—

Two hundred forty-five of 624 (39.3%) patients with CVT experienced presenting seizures, and 43 (6.9%) patients had early seizure. In logistic-regression analysis, supratentorial lesion (odds ratio [OR]=4.05, 95% CI=2.74 to 5.95), cortical vein thrombosis (OR=2.31, 95% CI=1.44 to 3.73), sagittal sinus thrombosis (OR=2.18, 95% CI=1.50 to 3.18), and puerperal CVT (OR=2.06, 95% CI=1.19 to 3.55) were associated with presenting seizures, whereas supratentorial lesion (OR=3.09, 95% CI=1.56 to 9.62) and presenting seizures (OR=1.74, 95% CI=0.90 to 3.37) predicted early seizures. The risk of early seizures in patients with supratentorial lesions and presenting seizures was significantly lower when AED prophylaxis was used (1 with seizures in 148 patients with AEDs vs 25 in 47 patients without AEDs; OR=0.006, 95% CI=0.001 to 0.05).

Conclusions—

CVT patients with supratentorial lesions had a higher risk for both presenting and early seizures, whereas patients with presenting seizures had a higher risk of recurrent seizures within 2 weeks. Our results support the prescription of AEDs in acute CVT patients with supratentorial lesions who present with seizures.
Autopsy Prevalence of Intracranial Atherosclerosis in Patients With Fatal Stroke
Authors: Mazighi Mikael , Labreuche Julien , Gongora-Rivera Fernando , Duyckaerts Charles , Hauw Jean-Jacques , Amarenco Pierre
Published: February 2008

Background and Purpose—

The objective of this study was to determine the prevalence of intracranial plaques and stenoses and their causal role in patients with fatal stroke. Intracranial atherosclerosis is considered to be a rare condition with a severe prognosis. However, disease prevalence may be underestimated due to lack of appropriate diagnostic procedures.

Methods—

We performed a systematic analysis of intra- and extracranial arteries, the aortic arch, and the heart in 339 consecutive autopsies of patients with stroke. Clinical history, risk factors, imaging data, and general autopsy reports were analyzed. Patients with brain hemorrhage (n=80) were used as control subjects.

Results—

Intracranial plaques and stenoses occurred in 62.2% (95% CI, 56.3 to 68.1) and 43.2% (95% CI, 37.2 to 49.3) of patients with brain infarction, respectively, compared with 48.8% (
P
<0.05) and 17.5% (
P
<0.001) of patients with brain hemorrhage, respectively. In the 43% of patients with brain infarction with at least one intracranial plaque-inducing luminal stenosis graded >30%, the stenosis was considered to be causal in 5.8% of cases (n=15) because of superimposed clot on ulcerated plaques; 27% of these patients had stenoses graded 30% to 75%. In multivariate analyses, diabetes and male sex were significantly associated with intracranial plaques and stenosis. History of myocardial infarction was significantly associated with intracranial plaques and previous stroke was associated with intracranial stenosis.

Conclusions—

Intracranial plaques and stenoses are highly prevalent in fatal stroke, and stenoses graded 30% to 75% may be causal. New arterial wall imaging techniques should be used to reevaluate the frequency and role of intracranial artery plaques in living patients with stroke.
Validation of a Prognostic Subarachnoid Hemorrhage Grading Scale Derived Directly From the Glasgow Coma Scale
Authors: van Heuven Annemarie W. , Dorhout Mees Sanne M. , Algra Ale , Rinkel Gabriel J.E.
Published: February 2008

Background and Purpose—

A new Glasgow Coma Scale-based scale has been developed to predict patient outcome in subarachnoid hemorrhage by calculating cut-off points by which 2 consecutive categories corresponded to a statistically significant different outcome. We assessed the external validity of this Prognosis on Admission of Aneurysmal Subarachnoid Hemorrhage (PAASH) scale and compared it to the commonly used World Federation of Neurological Surgeons scale.

Methods—

From our database of subarachnoid hemorrhage patients we retrieved data on all patients admitted between November 2000 and March 2006. By means of logistic regression, we calculated OR with corresponding 95% CI for poor outcome at 3 months for each category in comparison with the lowest category of both scales. Areas under the curve of the corresponding receiver operator characteristic curve were calculated.

Results—

We included 537 patients. For the PAASH scale, OR ranged from 3.9 (95% CI, 2.4 to 6.2) to 84 (95% CI, 25 to 287) and increased more evenly than for the World Federation of Neurological Surgeons (WFNS) scale, with OR ranging from 2.3 (95% CI, 1.3 to 4.1) to 69 (95% CI, 31 to 157). Areas under the curve were 0.81 (95% CI, 0.77 to 0.84) for the PAASH and 0.82 (95% CI, 0.79 to 0.86) for the WFNS scale.

Conclusion—

Both PAASH and WFNS scales have a good discriminatory ability for patient prognosis. Because the OR of the PAASH increase more gradually, it is slightly preferable to the WFNS scale.
Changes in Background Blood–Brain Barrier Integrity Between Lacunar and Cortical Ischemic Stroke Subtypes
Authors: Wardlaw Joanna M. , Farrall Andrew , Armitage Paul A. , Carpenter Trevor , Chappell Francesca , Doubal Fergus , Chowdhury Debashish , Cvoro Vera , Dennis Martin S.
Published: February 2008

Background and Purpose—

Lacunar stroke is associated with endothelial dysfunction and histologically with intrinsic cerebral microvascular disease of unknown cause. Endothelial dysfunction could impair blood–brain barrier integrity. We assessed background blood–brain barrier leakage in patients with lacunar ischemic stroke compared with cortical stroke controls.

Methods—

We recruited patients with lacunar or mild cortical ischemic stroke and assessed generalized cerebral blood–brain barrier leak with MRI and intravenous gadolinium at least 1 month after stroke. We used detailed image processing to compare signal change before and for 30 minutes postcontrast throughout gray matter, white matter, and cerebrospinal fluid with summary analyses and general linear modeling.

Results—

Among 48 patients (29 lacunar, 19 cortical), postcontrast enhancement was significantly higher in cerebrospinal fluid (
P
=0.04, Mann-Whitney
U
), and nonsignificantly higher in white matter, in lacunar than in cortical strokes, with no difference in gray matter. General linear modeling confirmed significantly greater postcontrast enhancement in cerebrospinal fluid in lacunar patients than in cortical controls (
t
=3.37,
P
<0.0008).

Conclusion—

These preliminary data suggest that the blood–brain barrier may be dysfunctional throughout subcortical white matter (white matter drains via interstitial spaces to cerebrospinal fluid) in patients with lacunar stroke. Further studies are required to confirm these findings and determine whether abnormal blood–brain barrier might predate development of lacunar disease. Blood–brain barrier dysfunction may be an important mechanism for brain damage in cerebral microvascular disease.
Risk of Aneurysmal Subarachnoid Hemorrhage
Authors: Jiménez-Yepes Carlos Mario , Londoño-Fernández Juan Luis
Published: February 2008

Background and Purpose—

From the studied variables in subarachnoid hemorrhage (SAH) risk, hypertension is probably the most controvertible one. The aim of this study was to determine whether confirmed hypertension, prospectively diagnosed with strict criteria, is an independent risk factor for aneurysmal SAH.

Methods—

A case-control study was conducted in 2 colombian cities between July 2004 and June 2005. There were 163 new cases of SAH (mean age 51 years; 107 were women) with 2 controls per case: 1 hospital and 1 community control. Hypertension was defined according to cardiovascular criteria, based on target organ damage. In addition to hypertension, other variables were studied: present smoking, recent alcohol consumption, alcohol dependency, coffee consumption, cocaine use, and body mass index. A multivariate logistic regression model was used to determine whether hypertension was an independent risk factor.

Results—

Among the studied variables, including confirmed hypertension, only present smoking became an independent risk factor for SAH.

Conclusions—

Confirmed hypertension is not an independent risk factor for aneurysmal SAH.
Predictive Models for the Breeder Genetic Algorithm I. Continuous Parameter Optimization
Authors: Mühlenbein Heinz , Schlierkamp-Voosen Dirk
Published: February 2008

In this paper a new genetic algorithm called the Breeder Genetic Algorithm (BGA) is introduced. The BGA is based on artificial selection similar to that used by human breeders. A predictive model for the BGA is presented that is derived from quantitative genetics. The model is used to predict the behavior of the BGA for simple test functions. Different mutation schemes are compared by computing the expected progress to the solution. The numerical performance of the BGA is demonstrated on a test suite of multimodal functions. The number of function evaluations needed to locate the optimum scales only as n ln(n) where n is the number of parameters. Results up to n = 1000 are reported.
Evolving Behaviors in the Iterated Prisoner's Dilemma
Authors: Fogel David B.
Published: February 2008

Evolutionary programming experiments are conducted to investigate the conditions that promote the evolution of cooperative behavior in the iterated prisoner's dilemma. A population of logical stimulus-response devices is maintained over successive generations with selection based on individual fitness. The reward for selfish behavior is varied across a series of trials. Simulations indicate three distinct patterns of behaviors in which mutual cooperation is inevitable, improbable, or apparently random. The ultimate behavior can be reliably predicted by examining the payoff matrix that defines the reward for alternative joint behaviors.
Implicit Niching in a Learning Classifier System: Nature's Way
Authors: Horn Jeffrey , Goldberg David E. , Deb Kalyanmoy
Published: February 2008

We approach the difficult task of analyzing the complex behavior of even the simplest learning classifier system (LCS) by isolating one crucial subfunction in the LCS learning algorithm: covering through niching. The LCS must maintain a population of diverse rules that together solve a problem (e.g., classify examples). To maintain a diverse population while applying the GAs selection operator, the LCS must incorporate some kind of niching mechanism. The natural way to accomplish niching in an LCS is to force competing rules to share resources (i.e., rewards). This implicit LCS fitness sharing is similar to the explicit fitness sharing used in many niched GAs. Indeed, the LCS implicit sharing algorithm can be mapped onto explicit fitness sharing with a one-to-one correspondence between algorithm components. This mapping is important because several studies of explicit fitness sharing, and of niching in GAs generally, have produced key insights and analytical tools for understanding the interaction of the niching and selection forces. We can now bring those results to bear in understanding the fundamental type of cooperation (a.k.a. weak cooperation) that an LCS must promote.
Scheduling of Genetic Algorithms in a Noisy Environment
Authors: Aizawa Akiko N. , Wah Benjamin W.
Published: February 2008

In this paper, we develop new methods for adjusting configuration parameters of genetic algorithms operating in a noisy environment. Such methods are related to the scheduling of resources for tests performed in genetic algorithms. Assuming that the population size is given, we address two problems related to the design of efficient scheduling algorithms specifically important in noisy environments. First, we study the durution-scheduling problem that is related to setting dynamically the duration of each generation. Second, we study the sample-allocation problem that entails the adaptive determination of the number of evaluations taken from each candidate in a generation. In our approach, we model the search process as a statistical selection process and derive equations useful for these problems. Our results show that our adaptive procedures improve the performance of genetic algorithms over that of commonly used static ones.
Tackling Car Sequencing Problems Using a Generic Genetic Algorithm
Authors: Warwick Terry , Tsang Edward P. K.
Published: February 2008

The car sequencing problem (CarSP) was seen as a challenge to artificial intelligence. The CarSP is a version of the job-shop scheduling problem, which is known to be NP-complete. The task in the CarSP is to schedule a given number of cars (of different types) in a sequence to allow the teams in each workstation on the assembly line to fit the required options (e.g. radio, sunroof) on the cars within the capacity of that workstation. In unsolvable problems, one would like to minimize the penalties associated with the violation of the capacity constraints. Previous attempts to tackle the problem either have been unsuccessful or have been restricted to solvable CarSPs only. In this paper, we report on promising results in applying a generic genetic algorithm, which we call GAcSP, to tackle both solvable and unsolvable CarSPs.
On the Relationship between the Duration of an Encounter and the Evolution of Cooperation in the Iterated Prisoner's Dilemma
Authors: Fogel David B.
Published: February 2008

Evolutionary programming experiments are conducted to examine the relationship between the durations of encounters and the evolution of cooperative behavior in the iterated prisoner's dilemma. A population of behavioral strategies represented by finite-state machines is evolved over successive generations, with selection made on the basis of individual fitness. Each finite-state machine is given an additional evolvable parameter corresponding to the maximum number of moves it will execute in any encounter. A series of Monte Carlo trials indicates distinct relationships between encounter length and cooperation; however, no causal relationship can be positively identified.
Modeling Simple Genetic Algorithms
Authors: Vose Michael D.
Published: February 2008

The infinite- and finite-population models of the simple genetic algorithm are extended and unified, The result incorporates both transient and asymptotic GA behavior. This leads to an interpretation of genetic search that partially explains population trajectories. In particular, the asymptotic behavior of the large-population simple genetic algorithm is analyzed.
Resource Allocation as an Evolving Strategy
Authors: Olafsson Sverrir
Published: February 2008

The efficient utilization of resources is an issue of essential importance in modern network management. The emergence of increasingly complicated and continuously changing network services requires softer and fuzzier methods in network management. In this paper we demonstrate how evolutionary game theory can be used for an efficient allocation of service requirements onto an ensemble of heterogeneous network components. By incorporating differentiated pricing structures into a system utility function, network agents are encouraged to increase their usage of those components that are presently badly utilized. It is demonstrated how this approach can enhance network utilization significantly. Some new results regarding evolutionarily stable strategies in nonlinear evolutionary games are also reported.
An Evolutionary Computing Approach to Probabilistic Reasoning on Bayesian Networks
Authors: Rojas-Guzmán Carlos , Kramer Mark A.
Published: February 2008

Bayesian belief networks can be used to represent and to reason about complex systems with uncertain or incomplete information. Bayesian networks are graphs capable of encoding and quantifying probabilistic dependence and conditional independence among variables. Diagnostic reasoning, also referred to as abductive inference, determining the most probable explanation (MPE), or finding the maximum a posteriori instantiation (MAP), involves determining the global most probable system description given the values of any subset of variables. In some cases abductive inference can be performed with exact algorithms using distributed network computations, but the problem is NP-hard, and complexity increases significantly with the presence of undirected cycles, the number of discrete states per variable, and the number of variables in the network. This paper describes an approximate method composed of a graph-based evolutionary algorithm that uses nonbinary alphabets, graphs instead of strings, and graph operators to perform abductive inference on multiply connected networks for which systematic search methods are not feasible. The motivation, basis, and adequacy of the method are discussed, and experimental results are presented.
Analysis of Selection Algorithms: A Markov Chain Approach
Authors: Chakraborty Uday Kumar , Deb Kalyanmoy , Chakraborty Mandira
Published: February 2008

A Markov chain framework is developed for analyzing a wide variety of selection techniques used in genetic algorithms (GAs) and evolution strategies (ESs). Specifically, we consider linear ranking selection, probabilistic binary tournament selection, deterministic s-ary (s = 3,4, …) tournament selection, fitness-proportionate selection, selection in Whitley's GENITOR, selection in (μ, λ)-ES, selection in (μ + λ)-ES, (μ, λ)-linear ranking selection in GAs, (μ + λ)-linear ranking selection in GAs, and selection in Eshelman's CHC algorithm. The analysis enables us to compare and contrast the various selection algorithms with respect to several performance measures based on the probability of takeover. Our analysis is exact—we do not make any assumptions or approximations. Finite population sizes are considered. Our approach is perfectly general, and following the methods of this paper, it is possible to analyze any selection strategy in evolutionary algorithms.
Using Learning to Facilitate the Evolution of Features for Recognizing Visual Concepts
Authors: Bala J. , Jong K. De , Huang J. , Vafaie H. , Wechsler H.
Published: February 2008

This paper describes a hybrid methodology that integrates genetic algorithms (GAs) and decision tree learning in order to evolve useful subsets of discriminatory features for recognizing complex visual concepts. A GA is used to search the space of all possible subsets of a large set of candidate discrimination features. Candidate feature subsets are evaluated by using C4.5, a decision tree learning algorithm, to produce a decision tree based on the given features using a limited amount of training data. The classification performance of the resulting decision tree on unseen testing data is used as the fitness of the underlying feature subset. Experimental results are presented to show how increasing the amount of learning significantly improves feature set evolution for difficult visual recognition problems involving satellite and facial image data. In addition, we also report on the extent to which other more subtle aspects of the Baldwin effect are exhibited by the system.
Logarithmic Convergence of Random Heuristic Search
Authors: Vose Michael D.
Published: February 2008

This paper speaks to the inherent emergent behavior of genetic search. For completeness and generality, a class of stochastic search algorithms, random heuristic search, is reviewed. A general convergence theorem for this class is then proved. Since the simple genetic algorithm (GA) is an instance of random heuristic search, a corollary is a result concerning GAs and time to convergence.
Learning to Control the Program Evolution Process with Cultural Algorithms
Authors: Zannoni Elena , Reynolds Robert G.
Published: February 2008

Traditional software engineering dictates the use of modular and structured programming and top-down stepwise refinement techniques that reduce the amount of variability arising in the development process by establishing standard procedures to be followed while writing software. This focusing leads to reduced variability in the resulting products, due to the use of standardized constructs. Genetic programming (GP) performs heuristic search in the space of programs. Programs produced through the GP paradigm emerge as the result of simulated evolution and are built through a bottom-up process, incrementally augmenting their functionality until a satisfactory level of performance is reached. Can we automatically extract knowledge from the GP programming process that can be useful to focus the search and reduce product variability, thus leading to a more effective use of the available resources? An answer to this question is investigated with the aid of cultural algorithms. A new system, cultural algorithms with genetic programming (CAGP), is presented. The system has two levels. The first is the pool of genetic programs (population level), and the second is a knowledge repository (belief set) that is built during the GP run and is used to guide the search process. The microevolution within the population brings about potentially meaningful characteristics of the programs for the achievement of the given task, such as properties exhibited by the best performers in the population. CAGP extracts these features and represents them as the set of the current beliefs. Beliefs correspond to constraints that all the genetic operators and programs must follow. Interaction between the two levels occurs in one direction through the extraction process and, in the other, through the modulation of an individual's program parameters according to which, and how many, of the constraints it follows. CAGP is applied to solve an instance of the symbolic regression problem, in which a function of one variable needs to be discovered. The results of the experiments show an overall improvement on the average performance of CAGP over GP alone and a significant reduction of the complexity of the produced solution. Moreover, the execution time required by CAGP is comparable with the time required by GP alone.
Empirical Investigation of Multiparent Recombination Operators in Evolution Strategies
Authors: Eiben Agoston E. , Bäck Thomas
Published: February 2008

An extension of evolution strategies to multiparent recombination involving a variable number ϱ of parents to create an offspring individual is proposed. The extension is experimentally evaluated on a test suite of functions differing in their modality and separability and the regular/irregular arrangement of their local optima. Multiparent diagonal crossover and uniform scanning crossover and a multiparent version of intermediary recombination are considered in the experiments. The performance of the algorithm is observed to depend on the particular combination of recombination operator and objective function. In most of the cases a significant increase in performance is observed as the number of parents increases. However, there might also be no significant impact of recombination at all, and for one of the unimodal objective functions, the performance is observed to deteriorate over the course of evolution for certain choices of the recombination operator and the number of parents. Additional experiments with a skewed initialization of the population clarify that intermediary recombination does not cause a search bias toward the origin of the coordinate system in the case of domains of variables that are symmetric around zero.
Evolutionary Consequences of Coevolving Targets
Authors: Pagie Ludo , Hogeweg Paulien
Published: February 2008

Most evolutionary optimization models incorporate a fitness evaluation that is based on a predefined static set of test cases or problems. In the natural evolutionary process, selection is of course not based on a static fitness evaluation. Organisms do not have to combat every existing disease during their lifespan; organisms of one species may live in different or changing environments; different species coevolve. This leads to the question of how information is integrated over many generations.

This study focuses on the effects of different fitness evaluation schemes on the types of genotypes and phenotypes that evolve. The evolutionary target is a simple numerical function. The genetic representation is in the form of a program (i.e., a functional representation, as in genetic programming). Many different programs can code for the same numerical function. In other words, there is a many-to-one mapping between “genotypes” (the programs) and “phenotypes”. We compare fitness evaluation based on a large static set of problems and fitness evaluation based on small coevolving sets of problems. In the latter model very little information is presented to the evolving programs regarding the evolutionary target per evolutionary time step. In other words, the fitness evaluation is very sparse. Nevertheless the model produces correct solutions to the complete evolutionary target in about half of the simulations. The complete evaluation model, on the other hand, does not find correct solutions to the target in any of the simulations. More important, we find that sparse evaluated programs are better generalizable compared to the complete evaluated programs when they are evaluated on a much denser set of problems. In addition, the two evaluation schemes lead to programs that differ with respect to mutational stability; sparse evaluated programs are less stable than complete evaluated programs.
Optimization of Road Networks Using Evolutionary Strategies
Authors: Schweitzer Frank , Ebeling Werner , Rosé Helge , Weiss Olaf
Published: February 2008

A road network usually has to fulfill two requirements: (i) it should as far as possible provide direct connections between nodes to avoid large detours; and (ii) the costs for road construction and maintenance, which are assumed proportional to the total length of the roads, should be low. The optimal solution is a compromise between these contradictory demands, which in our model can be weighted by a parameter. The road optimization problem belongs to the class of frustrated optimization problems. In this paper, a special class of evolutionary strategies, such as the Boltzmann and Darwin and mixed strategies, are applied to find differently optimized solutions (graphs of varying density) for the road network, depending on the degree of frustration. We show that the optimization process occurs on two different time scales. In the asymptotic limit, a fixed relation between the mean connection distance (detour) and the total length (costs) of the network exists that defines a range of possible compromises. Furthermore, we investigate the density of states, which describes the number of solutions with a certain fitness value in the stationary regime. We find that the network problem belongs to a class of optimization problems in which more effort in optimization certainly yields better solutions. An analytical approximation for the relation between effort and improvement is derived.
Genetic Forma Recombination in Permutation Flowshop Problems
Authors: Cotta Carlos , Troya José M.
Published: February 2008

This paper analyzes different representations for permutation flowshop problems. This is done using forma analysis to assess the quality of these representations with respect to makespan optimization. Classical recombination operators are studied and empirically evaluated in this context. It is shown that the best operators work on representations in which absolute positions of tasks are relevant. Subsequently, some new operators operating on these representations are proposed. These new operators are designed to exhibit specific properties regarding implicit mutation and forma transmission. Their performance is shown to be competitive with traditional operators.
Adapting Operator Settings in Genetic Algorithms
Authors: Tuson Andrew , Ross Peter
Published: February 2008

In the majority of genetic algorithm implementations, the operator settings are fixed throughout a given run. However, it has been argued that these settings should vary over the course of a genetic algorithm run—so as to account for changes in the ability of the operators to produce children of increased fitness. This paper describes an investigation into this question. The effect upon genetic algorithm performance of two adaptation methods upon both well-studied theoretical problems and a hard problem from operations research, the flowshop sequencing problem, are therefore examined. The results obtained indicate that the applicability of operator adaptation is dependent upon three basic assumptions being satisfied by the problem being tackled.
Code Growth, Explicitly Defined Introns, and Alternative Selection Schemes
Authors: Smith Peter W. H. , Harries Kim
Published: February 2008

Previous work on introns and code growth in genetic programming is expanded on and tested experimentally. Explicitly defined introns are introduced to tree-based representations as an aid to measuring and evaluating intron behavior. Although it is shown that introns do create code growth, they are not its only cause. Removing introns merely decreases the growth rate; it does not eliminate it. By systematically negating various forms of intron behavior, a deeper understanding of the causes of code growth is obtained, leading to the development of a system that keeps unnecessary bloat to a minimum. Alternative selection schemes and recombination operators are examined and improvements demonstrated over the standard selection methods in terms of both performance and parsimony.
FOX-GA: A Genetic Algorithm for Generating and Analyzing Battlefield Courses of Action
Authors: Schlabach J. L. , Hayes C. C. , Goldberg D. E.
Published: February 2008

This paper describes FOX-GA, a genetic algorithm (GA) that generates and evaluates plans in the complex domain of military maneuver planning. FOX-GA's contributions are to demonstrate an effective application of GA technology to a complex real world planning problem, and to provide an understanding of the properties needed in a GA solution to meet the challenges of decision support in complex domains. Previous obstacles to applying GA technology to maneuver planning include the lack of efficient algorithms for determining the fitn ess of plans. Detailed simulations would ideally be used to evaluate these plans, but most such simulations typically require several hours to assess a single plan. Since a GA needs to quickly generate and evaluate thousands of plans, these methods are too slow. To solve this problem we developed an efficient evaluator (wargamer) that uses course-grained representations of this problem domain to allow appropriate yet intelligent trade-offs between computational efficiency and accuracy. An additional challenge was that users needed a diverse set of significantly different plan options from which to choose. Typical GA's tend to develop a group of “best” solutions that may be very similar (or identical) to each other. This may not provide users with sufficient choice. We addressed this problem by adding a niching strategy to the selection mechanism to insure diversity in the solution set, providing users with a more satisfactory range of choices. FOX-GA's impact will be in providing decision support to time constrained and cognitively overloaded battlestaff to help them rapidly explore options, create plans, and better cope with the information demands of modern warfare.
Predicting Epistasis from Mathematical Models
Authors: Heckendorn Robert B. , Whitley Darrell
Published: February 2008

Classically, epistasis is either computed exactly by Walsh coefficients or estimated by sampling. Exact computation is usually of theoretical interest since the computation typically grows exponentially with the number of bits in the domain. Given an evaluation function, epistasis also can be estimated by sampling. However this approach gives us little insight into the origin of the epistasis and is prone to sampling error.

This paper presents theorems establishing the bounds of epistasis for problems that can be stated as mathematical expressions. This leads to substantial computational savings for bounding the difficulty of a problem. Furthermore, working with these theorems in a mathematical context, one can gain insight into the mathematical origins of epistasis and how a problem's epistasis might be reduced. We present several new measures for epistasis and give empirical evidence and examples to demonstrate the application of the theorems. In particular, we show that some functions display “parity” such that by picking a well-defined representation, all Walsh coefficients of either odd or even index become zero, thereby reducing the nonlinearity of the function.
Schemata Evolution and Building Blocks
Authors: Stephens Chris , Waelbroeck Henri
Published: February 2008

In the light of a recently derived evolution equation for genetic algorithms we consider the schema theorem and the building block hypothesis. We derive a schema theorem based on the concept of effective fitness showing that schemata of higher than average effective fitness receive an exponentially increasing number of trials over time. The equation makes manifest the content of the building block hypothesis showing how fit schemata are constructed from fit sub-schemata. However, we show that, generically, there is no preference for short, low-order schemata. In the case where schema reconstruction is favored over schema destruction, large schemata tend to be favored. As a corollary of the evolution equation we prove Geiringer's theorem.
Evolution Determined by Trajectory of Expected Populations: Sufficient Conditions, with Application to Crossover
Authors: Bruce I. Douglas , Simpson R. Jamie
Published: February 2008

The study of a population's evolution under the action of a genetic operator, or composition of operators, is more difficult when the population size is finite because the examination of the expected population at each generation does not necessarily yield the overall expected result. In certain circumstances, some interesting properties of a population change during evolution in such a way that a valid conclusion can be drawn by charting the change from expected population to expected population. We establish sufficient conditions that ensure that the evolution of a property of a population can be determined by examination of the expected populations only. An example of the application of this characterization is a proof that a finite size population under repeated crossover in the absence of selection or mutation converges, in the sense of expected outcome, to the population with maximum diversity. The proof extends the results already established by others for infinite populations.
The Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of Populations
Authors: Harik George , Cantú-Paz Erick , Goldberg David E. , Miller Brad L.
Published: February 2008

This paper presents a model to predict the convergence quality of genetic algorithms based on the size of the population. The model is based on an analogy between selection in GAs and one-dimensional random walks. Using the solution to a classic random walk problem—the gambler's ruin—the model naturally incorporates previous knowledge about the initial supply of building blocks (BBs) and correct selection of the best BB over its competitors. The result is an equation that relates the size of the population with the desired quality of the solution, as well as the problem size and difficulty. The accuracy of the model is verified with experiments using additively decomposable functions of varying difficulty. The paper demonstrates how to adjust the model to account for noise present in the fitness evaluation and for different tournament sizes.
A Statistical Study of a Class of Cellular Evolutionary Algorithms
Authors: Capcarrère Mathieu , Tomassini Marco , Tettamanzi Andrea , Sipper Moshe
Published: February 2008

Parallel evolutionary algorithms, over the past few years, have proven empirically worthwhile, but there seems to be a lack of understanding of their workings. In this paper we concentrate on cellular (fine-grained) models, our objectives being: (1) to introduce a suite of statistical measures, both at the genotypic and phenotypic levels, which are useful for analyzing the workings of cellular evolutionary algorithms; and (2) to demonstrate the application and utility of these measures on a specific example—the cellular programming evolutionary algorithm. The latter is used to evolve solutions to three distinct (hard) problems in the cellular-automata domain: density, synchronization, and random number generation. Applying our statistical measures, we are able to identify a number of trends common to all three problems (which may represent intrinsic properties of the algorithm itself, as well as a host of problem-specific features. We find that the evolutionary algorithm tends to undergo a number of phases which we are able to quantitatively delimit. The results obtained lead us to believe that the measures presented herein may prove useful in the general case of analyzing fine-grained evolutionary algorithms.
Crossover Accelerates Evolution in GAs with a Babel-like Fitness Landscape: Mathematical Analyses
Authors: Suzuki Hideaki , Iwasa Yoh
Published: February 2008

The effectiveness of crossover in accelerating evolution in genetic algorithms (GAs) is studied with a haploid finite population of bit sequences. A Babel-like fitness landscape is assumed. There is a single bit sequence (schema) that is significantly more advantageous than all the others. We study the time until domination of the advantageous schema (Td). Evolution proceeds with appearance, spread, and domination of the advantageous schema. The most important process determining Tdis the appearance (creation) of the advantageous schema. Crossover helps this creation process and enhances the rate of evolution. To study this effect, we first establish an analytical method to estimate Tdwith or without crossover. Then, we conduct a numerical analysis using the frequency vector representation of the population with the recurrence relations formulated after GA operations. Finally, we carry out direct computer simulations with simple GAs operating on a population of binary strings directly prepared in the computer memory to examine the performance of the two analytical methods. It is shown that Tdis reduced greatly by crossover with a mildly high rate when the mutation rate is adjusted to a moderate value and that an advantageous schema has a fairly large order (the number of bits). From these observations, we can determine implementation criteria for GAs, which are useful when we applying GAs to engineering problems having a conspicuously discontinuous fitness landscape.