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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Personalized Risk Assesment for Adverse Drug Reactions and Treatment Failures

As NASA and other space agencies prepare for future long-term space missions beyond the LEO, the cumulative impact of risk factors encountered in space increases substantially rising concerns about astronauts health. Application of on-board medications to mitigate clinical symptoms associated with certain medical conditions and illnesses is the first line of response to ensure sustainable health and performance of crew. Unfortunately, very limited research has been conducted to determine efficacy of the earth-based pharmaceuticals in a microgravity environment. In some instances, orally administered medications taken during flight were reported to be less effective than expected. Evaluation of series of experiments involving astronauts from shuttle flights shows notable individual variability to several pharmaceuticals during flight. These data provide reasonable assumption of perturbation in CYP450 enzymes during spaceflight, which contribute to the hepatic metabolism of the majority of drugs and therefore may have significant effects on therapeutic efficacy and increase treatment-related toxicity. The genes encoding the CYP450 enzymes are highly variable in humans. Inheritable variations of CYP450 hepatic metabolizer enzymes and transport proteins play a crucial role in the inter-individual variability of drug efficiency and risks of adverse drug reactions. Additionally, there are some reports that document changes in the levels of production of drug-metabolizing enzymes in microgravity. Therefore, in order to provide a safe and effective pharmaceutical treatment in space, medications selection should be based not only on the specific efficacy of medications but also on the individual drug sensitivity and flight-induced changes in metabolism of astronauts chosen for a particular mission. To our knowledge, there was no pre-flight drug sensitivity testing on a genetic level for any of the previous manned NASA space missions. Therefore, technologies capable of predicting and managing medication efficacy, side effects, and toxicity of drugs based on individual genetic variability of crew members are increasingly needed. In this report, we present results of testing the market available Personalized Prescribing System (PPS), a comprehensive, non-invasive solution for safer, targeted medication management for every crew member. Statistical accuracy and simplicity of non-invasive sample analysis demonstrate the feasibility of drug sensitivity assessment and record-keeping tool for flight surgeons and astronauts in applying the recommended medications for situations arising in flight. The information on individual drug sensitivity will translate into personalized risk assessment for adverse drug reactions and treatment failures for each drug from the medication kit as well as predefined outcome. This will address the HHC’s raised “Concern of Clinically Relevant Unpredicted Effects of Medication” as recently updated.

medications↗
DOE OSTI2025

Multi-Objective Optimization of Uranium Target Assembly–3: A Comparison of Genetic and Traditional Methods

Commonly produced as a byproduct of uranium fission, 99 Mo is a key medical isotope that is in high demand in the United States. An international goal is to switch from medical isotope production technologies that require highly enriched uranium to medical isotope production technologies that require only low-enriched uranium. Niowave Inc. is contributing to this goal by developing an accelerator-driven subcritical assembly called the Uranium Target Assembly (UTA). This work compares the performance of Dakota’s Multi-Objective Genetic Algorithm (MOGA) against traditional sensitivity analysis in the neutronic optimization of the UTA-3 system. The design objectives are k-eigenvalue (k eff ) and natural uranium fission power, which are directly correlated with the amount of 99 Mo produced. Dakota:MOGA did not perform as well as human engineering ingenuity in optimization studies with high numbers of input parameters, such as fuel rod type selection and fuel rod placement. However, Dakota:MOGA did outperform traditional sensitivity analysis in optimization studies with fewer than 20 parameters and revealed the degree to which each parameter influences the optimal design space for k eff and natural uranium fission power (to a lesser extent). As the design model became more complex in the final stage of design, the computational resources required to calculate the design objective values in the Monte Carlo N-Particle transport code from selected input parameter combinations limited Dakota:MOGA’s performance, and, unfortunately, human intervention was required to discern the optimal design space. In conclusion, future work will attempt to reduce computational resource constraints by incorporating areduced-order neutronics model into the optimization cycle.

Accelerator-driven systems↗
NASA NTRS1966

Biology and the Exploration of Mars

Until recent years the origin of life and its possible occurrence elsewhere in the universe have been matters for speculation only. The rapid growth of molecular biology since 1940 has, to be sure, made it possible to discuss life's origins in far more precise and explicit terms than was possible earlier; and the subject entered a new experimental phase in the 1950's with successful abiogenic synthesis of important biochemical substances in conditions simulating the presumptive environment of the primitive Earth. But the real transformation that the subject has undergone stems from the spectacular growth of space technology in the last decade. The possibility of life's origin and occurrence on planets other than ours is no longer limited to idle speculation: it has entered the realm of the testable, of science in the strict sense. Given the rockets now available, and especially those available by 1969, it has become fully realistic to consider plans for the biological exploration of Mars. The study that this report seeks to interpret was initiated in June, 1964, by the Space Science Board of the National Academy of Sciences to examine this possibility. The working group comprised 36 people representing a broad spectrum of scientific interests: evolutionary biology, genetics, microbiology, biochemistry and molecular biology, animal physiology, soil chemistry, organic chemistry, planetary astronomy, geochemistry, and theoretical physics. The participants included some with considerable prior involvement in problems of space exploration and others with none. Advice was also sought outside the group of immediate participants on the potentialities of selected analytical methods for the experimental study of extraterrestrial life and its environment. More than 30 individuals contributed in this fashion written assessments of techniques in which they were particularly well versed. Our task was to examine the scientific foundations and merits of the proposal to undertake a biological exploration of Mars. What are the potential scientific yields? How valuable, if attained, would they be? What, in fact, is the possibility of life occurring on Mars? And of our detecting it with available and foreseeable technology? What could be achieved by further astronomical work from Earth? by Martian fly-by missions? by Martian orbiters? and Martian Landers? What payloads would we recommend for planetary missions? What timing and over-all strategy would we recommend for Martian exploration were we to consider it worthwhile at all? In brief, the over-all purpose was to recommend to. the government, through the Academy's Space Science Board, whether or not a biological exploration of Mars should be included in the nation's space program over the next few decades; and, further, to outline what that program, if any, should be.

CONFERENCE↗
NASA NTRS2009

Validity of the Aluminum Equivalent Approximation in Space Radiation Shielding

The origin of the aluminum equivalent shield approximation in space radiation analysis can be traced back to its roots in the early years of the NASA space programs (Mercury, Gemini and Apollo) wherein the primary radiobiological concern was the intense sources of ionizing radiation causing short term effects which was thought to jeopardize the safety of the crew and hence the mission. Herein, it is shown that the aluminum equivalent shield approximation, although reasonably well suited for that time period and to the application for which it was developed, is of questionable usefulness to the radiobiological concerns of routine space operations of the 21 st century which will include long stays onboard the International Space Station (ISS) and perhaps the moon. This is especially true for a risk based protection system, as appears imminent for deep space exploration where the long-term effects of Galactic Cosmic Ray (GCR) exposure is of primary concern. The present analysis demonstrates that sufficiently large errors in the interior particle environment of a spacecraft result from the use of the aluminum equivalent approximation, and such approximations should be avoided in future astronaut risk estimates. In this study, the aluminum equivalent approximation is evaluated as a means for estimating the particle environment within a spacecraft structure induced by the GCR radiation field. For comparison, the two extremes of the GCR environment, the 1977 solar minimum and the 2001 solar maximum, are considered. These environments are coupled to the Langley Research Center (LaRC) deterministic ionized particle transport code High charge (Z) and Energy TRaNsport (HZETRN), which propagates the GCR spectra for elements with charges (Z) in the range I <= Z <= 28 (H -- Ni) and secondary neutrons through selected target materials. The coupling of the GCR extremes to HZETRN allows for the examination of the induced environment within the interior' of an idealized spacecraft as approximated by a spherical shell shield, and the effects of the aluminum equivalent approximation for a good polymeric shield material such as genetic polyethylene (PE). The shield thickness is represented by a 25 g/cm spherical shell. Although one could imagine the progression to greater thickness, the current range will be sufficient to evaluate the qualitative usefulness of the aluminum equivalent approximation. Upon establishing the inaccuracies of the aluminum equivalent approximation through numerical simulations of the GCR radiation field attenuation for PE and aluminum equivalent PE spherical shells, we Anther present results for a limited set of commercially available, hydrogen rich, multifunctional polymeric constituents to assess the effect of the aluminum equivalent approximation on their radiation attenuation response as compared to the generic PE.

Badavi, Francis F.↗
NASA NTRS2023

Wheat Crop Traits Conferring High Yield Potential May Also Improve Yield Stability Under Climate Change

Increasing genetic wheat yield potential is considered by many as critical to increasing global wheat yields and production, baring major changes in consumption patterns. Climate change challenges breeding by making target environments less predictable, altering regional productivity and potentially increasing yield variability. Here we used a crop simulation model solution in the SIMPLACE framework to explore yield sensitivity to select trait characteristics (radiation use efficiency [RUE], fruiting efficiency and light extinction coefficient) across 34 locations representing the world’s wheat-producing environments, determining their relationship to increasing yields, yield variability and cultivar performance. The magnitude of the yield increase was trait-dependent and differed between irrigated and rainfed environments. RUE had the most prominent marginal effect on yield, which increased by about 45 % and 33 % in irrigated and rainfed sites, respectively, between the minimum and maximum value of the trait. Altered values of light extinction coefficient had the least effect on yield levels. Higher yields from improved traits were generally associated with increased inter-annual yield variability (measured by standard deviation), but the relative yield variability (as coefficient of variation) remained largely unchanged between base and improved genotypes. This was true under both current and future climate scenarios. In this context, our study suggests higher wheat yields from these traits would not increase climate risk for farmers and the adoption of cultivars with these traits would not be associated with increased yield variability.

Climate change↗
DOE OSTI2026

Climate change drives convergent evolution of root traits on Sky Island climate relicts

Roots are essential to the strategies plants use to survive in variable environments, yet we know little of how they vary within species. Experimental conditions demonstrate that intraspecific plant root traits respond strongly to variation in the environment; however, it is unclear when these responses can be characterized as evolution in response to selective pressures of climate change over many generations. Sky Islands are model, natural climate relict ecosystems to examine climate-change driven evolution. Utilizing a common garden with replicate genotypes of Populus angustifolia (Narrowleaf cottonwood) from six Sky Island (SI) populations and nine adjacent Mountain Chain (MC) populations across three genetic provenances, we hypothesized that SI root traits have diverged due to historical isolation in warmer, drier climates. When grown in common conditions, populations originating on SI’s showed convergent evolution across three distinct genetic provenances, which was characterized by 44.16% decreased total root length, 42.64% decreased average root volume, 43.31% decreased root surface area, and significantly less root trait variation, relative to adjacent mountain chains. Convergent evolution of root traits from trees originating on SI’s is correlated with changes in mean annual precipitation and potential evapotranspiration in the field over the past ~ 125 years. These results demonstrate a consistent pattern in root trait evolution at the landscape scale and the role of climate on the evolution of root traits in a genetic and geographic context relevant to climate change.

Convergent evolution↗
DOE OSTI2025

Optimizing genomic prediction for complex traits via investigating multiple factors in switchgrass

Genomic prediction has accelerated breeding processes and provided mechanistic insights into the genetic bases of complex traits. To further optimize genomic prediction, we assess the impact of genome assemblies, genotyping approaches, variant types, allelic complexities, polyploidy levels, and population structures on the prediction of 20 complex traits in switchgrass (Panicum virgatum L.), a perennial biofuel feedstock. Surprisingly, short read-based genome assembly performs comparably to or even better than long read-based assembly. Due to higher gene coverage, exome capture and multi-allelic variants outperform genotyping-by-sequencing and bi-allelic variants, respectively. Tetraploid models show higher prediction accuracy than octoploid models for most traits, likely due to the greater genetic distances among tetraploids. Depending on the trait in question, different types of variants need to be integrated for optimal predictions. Furthermore, our study provides insights into the factors influencing genomic prediction outcomes, guiding best practices for future studies and for improving agronomic traits in switchgrass and other species through selective breeding.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Yeast Strain Development and Hardware Testing in Preparation of a Lunar BioSensor

With Artemis missions underway, it is clear we are going back to the Moon to stay. Before sending Astronauts for long-duration missions, it is crucial to understand the technological and biomedical countermeasures needed to protect them before they get there. We can use knowledge gained from biological CubeSats to guide the next generation of experiments to support human habitation on the Moon. Lunar Explorer Instrument for space biology Applications (LEIA) is NASA’s latest BioSensor, adapted BioSentinel, the only CubeSat to travel Beyond Low Earth Orbit. BioSentinel launched on Artemis I and is currently >50 million kilometers from Earth (as of July 2024). LEIA aims to identify biological responses to the Lunar environment, which unprotected against would pose a threat to astronauts (cancer, cardiovascular disease, neurological impairment). The suite of instruments within LEIA detects Lunar radiation using two on-board radiation sensors (ARES charged particle detector, Mini-Fast Neutron Detector), then monitors real-time biological responses to the Lunar environment via an autonomous microfluidic system, fit with 3-LED emitter and detector boards and the alamarBlue metabolic indicator dye. LEIA will use a genetic approach in addition to synthetic biology to test counter-measure production in space, with the goal to inform and protect astronauts for future Moon missions. We have conducted preliminary tests in preparation for launch to the anticipated South Pole of the Moon, optimizing the biology (strain down-selection, desiccation tolerance, radiation sensitivity) and improving the hardware (including a blue LED to detect the beta-carotene countermeasure product). Our team will discuss these findings in several parts – an overview of the LEIA mission (Mark Settles), adapting flexible CubeSat platforms for deep-space applications (Sergio Santa Maria, Kira Rienecker), developing new technologies to support LEIA ground studies (Chinmayee Govinda Raj), and yeast strain development and hardware testing in preparation for LEIA (presented here).

synthetic biology↗
DOE OSTI2025

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement

This work describes a blueprint for a process that accelerates progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application-driven experiments to maximally reduce pertinent data uncertainties? Answering this question entails solving a high-dimensional and complex optimization problem that is best solved with advanced statistic techniques often classified as machine learning. We apply this process within the framework of nuclear data with the aim to select an experiment combination that will reduce uncertainties in 239 Pu nuclear data for neutron energies between 1 and 600 keV. In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to 239 Pu fission cross sections in the desired energy range. Twenty-three candidate differential experiments were investigated and span multiple nuclear physics observables (e.g., total, capture cross sections) for isotopes appearing in the integral experiments. The optimal combination among these candidate experiments was investigated via generalized least squares fitting, augmented with Gaussian processes to ameliorate statistical irregularities in data, and the D-optimality criterion. The latter evaluates for each pair of candidates the joint reduction in uncertainties of all 12200 nuclear data appearing in the integral experiments compared to the knowledge we have from 168 past experiments, theory, and nuclear data. We chose as differential measurements those that investigate 63 Cu and 239 Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al 2 ⁢O 3 and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2002

Life Out of Chaos

Doctinary overlays on the definition of life can effectively be avoided by focusing discussion on microorganisms, their vital processes, and their genetic pedigree. To reach beyond these present and highly advanced forms of life and to inquire about its origin it is necessary to consider the requirements imposed by the environment. These requirements include geophysically and geochemically acceptable conjectures for the generation of source compounds, their concentration from dilute solution, and their selective combination into functional biomolecules. For vital function these macromolecules require programming in the form of specific sequence motifs. This critical programming constitutes the scientifically least understood process in the origin of life. Once this stage has been surpassed the laws of Darwinian evolution can operate in ways that are understood and experimentally demonstrated.

Arrhenius, Gustaf↗
NASA NTRSDate not supplied

Bioreactor Development for CO2-Based In Situ Resource Utilization Manufacturing

Sustainable long-duration manned missions on both the Moon and Mars will require in situ resource utilization (ISRU). Carbon dioxide (CO2) has great potential as a harvestable resource, making up 95% of the atmosphere on Mars and being produced as respiratory waste in spacecraft and future planetary habitats. Through ISRU, biomanufacturing has the capability to produce a near limitless array of products from local space resources. Here, a CO2-based ISRU recombinant protein producing bioreactor and associated biomanufacturing organisms were designed to produce a highly stable carbonic anhydrase (CA). Candidate organisms were selected by growth characterization on acetate and formic acid, carbon substrates that are synthesized via electrochemical conversion of CO2. To improve growth on the CO2 producing substrate formic acid and for direct integration of ISRU CO2, a synthetic Calvin-Benson-Bassam cycle was designed for use in Escherichia coli. Multiplex genetic modification in E. coli was facilitated by a tailored CRISPR/Cas9 and λ red recombineering two-vector system. For expression of CA, a blue light regulated T7 promoter was employed for dynamic and small molecule free induction. Efficient bioproduction through a fed-batch exponential feeding strategy was determined via mass balance analysis from ISRU substrates to biomass and CA yield. Flux balance analysis was used to model ISRU substrate metabolism and metabolic pathway engineering in candidate organisms under cultivation strategy conditions for both metabolism reconstruction and pathway design optimization. Finally, a small-scale, disposable bag bioreactor for use in the NASA Bioculture System infrastructure was designed to enable CO2-based CA biomanufacturing in reduced-gravity environments.

biomanufacturing↗
NASA NTRS2006

Three-Function Logic Gate Controlled by Analog Voltage

The figure is a schematic diagram of a complementary metal oxide/semiconductor (CMOS) electronic circuit that performs one of three different logic functions, depending on the level of an externally applied control voltage, V(sub sel). Specifically, the circuit acts as A NAND gate at V(sub sel) = 0.0 V, A wire (the output equals one of the inputs) at V(sub sel) = 1.0 V, or An AND gate at V(sub sel) = -1.8 V. [The nominal power-supply potential (VDD) and logic "1" potential of this circuit is 1.8 V.] Like other multifunctional circuits described in several prior NASA Tech Briefs articles, this circuit was synthesized following an automated evolutionary approach that is so named because it is modeled partly after the repetitive trial-and-error process of biological evolution. An evolved circuit can be tested by computational simulation and/or tested in real hardware, and the results of the test can provide guidance for refining the design through further iteration. The evolutionary synthesis of electronic circuits can now be implemented by means of a software package Genetic Algorithms for Circuit Synthesis (GACS) that was developed specifically for this purpose. GACS was used to synthesize the present trifunctional circuit. As in the cases of other multifunctional circuits described in several prior NASA Tech Briefs articles, the multiple functionality of this circuit, the use of a single control voltage to select the function, and the automated evolutionary approach to synthesis all contribute synergistically to a combination of features that are potentially advantageous for the further development of robust, multiple-function logic circuits, including, especially, field-programmable gate arrays (FPGAs). These advantages include the following: This circuit contains only 9 transistors about half the number of transistors that would be needed to obtain equivalent NAND/wire/AND functionality by use of components from a standard digital design library. If multifunctional gates like this circuit were used in the place of the configurable logic blocks of present commercial FPGAs, it would be possible to change the functions of the resulting digital systems within shorter times. For example, by changing a single control voltage, one could change the function of thousands of FPGA cells within nanoseconds. In contrast, typically, the reconfiguration in a conventional FPGA by use of bits downloaded from look-up tables via a digital bus takes microseconds.

Zebulum, Ricardo↗
NASA NTRS1979

Selective formation of microparticles by homopolyribonucleotides and proteinoids rich in individual amino acis

The formation of phase-separated microparticles following the mixing of solutions of homopolyribonucleotides with solutions of several basic thermal proteinoids, each rich in an individual amino acid, has been studied. Three of the 4 proteinoids studied yielded results consistent with a matrix of anticodonicity; the fourth did not. The meaning of these results, and others, relative to a postulated matrix for the genetic coding mechanism is discussed.

Lacey, J. C., Jr.↗
DOE OSTI2024

Identifying a novel pathway for extracellular electron uptake in Methanosarcina barkeri using shotgun

The overarching goal of this project was to identify the genetic and/or enzymatic basis for extracellular electron uptake in Methanosarcina barkeri—an organism we previously characterized to be capable of this process using poised potential electrodes and a range of electrochemical techniques. In our first aim, we will utilized proteomic techniques that labels extracellular proteins with free amine groups with biotin and perform a selective purification of these proteins from the rest of the proteome. These were identified using mass spectrometry, providing us insight into the identity of the cell surface proteins, including redox active proteins present during extracellular electron uptake. We will also used an isobaric tagging technique (iTRAQ labeling) of proteomes from different experiment conditions to look at differential proteins expression and better understand the total pathway involved in extracellular electron uptake coupled to methanogenesis. In our final aim, we will investigated the electrochemical nature of electron uptake in co-cultures, compared to our pure culture data sets. We predict the process of electron uptake from electrodes replicates what goes on in nature when these organisms for co-cultures with electrogenic microbes such as Geobacter, and to test this hypothesis we have begun to probe co-cultures electrochemically during direct interspecies electron transfer. Our final aim took much longer than expected due to challenges replicating co-cultures between Geobacter metallireducens and Methanosarcina barkeri. We found the major problem with this work was the inability of the M. barkeri strain we used (and we tried strains from three different labs) to successfully grow on acetate in the absence of hydrogen. As such, we began to use the strain Methanosarcina acetivorans—another close relative that specializes on acetate growth. We are currently in the process of comparing electrochemical observations of this microorganism between pure and co-culture experiments.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1990

Genetic-evolution-based optimization methods for engineering design

This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

Rao, S. S.↗
DOE OSTI2024

Extreme elevational migration spurred cryptic speciation in giant hummingbirds

The ecoevolutionary drivers of species niche expansion or contraction are critical for biodiversity but challenging to infer. Niche expansion may be promoted by local adaptation or constrained by physiological performance trade-offs. For birds, evolutionary shifts in migratory behavior permit the broadening of the climatic niche by expansion into varied, seasonal environments. Broader niches can be short-lived if diversifying selection and geography promote speciation and niche subdivision across climatic gradients. To illuminate niche breadth dynamics, we can ask how “outlier” species defy constraints. Of the 363 hummingbird species, the giant hummingbird (Patagona gigas) has the broadest climatic niche by a large margin. To test the roles of migratory behavior, performance trade-offs, and genetic structure in maintaining its exceptional niche breadth, we studied its movements, respiratory traits, and population genomics. Satellite and light-level geolocator tracks revealed an >8,300-km loop migration over the Central Andean Plateau. This migration included a 3-wk, ~4,100-m ascent punctuated by upward bursts and pauses, resembling the acclimatization routines of human mountain climbers, and accompanied by surging blood-hemoglobin concentrations. Extreme migration was accompanied by deep genomic divergence from high-elevation resident populations, with decisive postzygotic barriers to gene flow. The two forms occur side-by-side but differ almost imperceptibly in size, plumage, and respiratory traits. The high-elevation resident taxon is the world’s largest hummingbird, a previously undiscovered species that we describe and name here. The giant hummingbirds demonstrate evolutionary limits on niche breadth: when the ancestral niche expanded due to evolution (or loss) of an extreme migratory behavior, speciation followed.

Science & Technology - Other Topics↗
NASA NTRS1999

Co-evolution for Problem Simplification

This paper explores a co-evolutionary approach applicable to difficult problems with limited failure/success performance feedback. Like familiar "predator-prey" frameworks this algorithm evolves two populations of individuals - the solutions (predators) and the problems (prey). The approach extends previous work by rewarding only the problems that match their difficulty to the level of solut,ion competence. In complex problem domains with limited feedback, this "tractability constraint" helps provide an adaptive fitness gradient that, effectively differentiates the candidate solutions. The algorithm generates selective pressure toward the evolution of increasingly competent solutions by rewarding solution generality and uniqueness and problem tractability and difficulty. Relative (inverse-fitness) and absolute (static objective function) approaches to evaluating problem difficulty are explored and discussed. On a simple control task, this co-evolutionary algorithm was found to have significant advantages over a genetic algorithm with either a static fitness function or a fitness function that changes on a hand-tuned schedule.

Haith, Gary L.↗