Competitive Evolution Research Articles

Global progress in competitive co-evolution: a systematic comparison of alternative methods.

The usage of broad sets of training data is paramount to evolve adaptive agents. In this respect, competitive co-evolution is a widespread technique in which the coexistence of different learning agents fosters adaptation, which in turn makes agents experience continuously varying environmental conditions. However, a major pitfall is related to the emergence of endless limit cycles where agents discover, forget and rediscover similar strategies during evolution. In this work, we investigate the use of competitive co-evolution for synthesizing progressively better solutions. Specifically, we introduce a set of methods to measure historical and global progress. We discuss the factors that facilitate genuine progress. Finally, we compare the efficacy of four qualitatively different algorithms, including two newly introduced methods. The selected algorithms promote genuine progress by creating an archive of opponents used to evaluate evolving individuals, generating archives that include high-performing and well-differentiated opponents, identifying and discarding variations that lead to local progress only (i.e., progress against the opponents experienced and retrogressing against others). The results obtained in a predator-prey scenario, commonly used to study competitive evolution, demonstrate that all the considered methods lead to global progress in the long term. However, the rate of progress and the ratio of progress versus retrogressions vary significantly among algorithms. In particular, our outcomes indicate that the Generalist method introduced in this work outperforms the other three considered methods and represents the only algorithm capable of producing global progress during evolution.

Evolution of transport, accessibility and tourism competitiveness in Extremadura (Spain): a benchmarking analysis

The efficiency of the transportation options available to tourists, in terms of convenience and time, directly impacts the competitiveness of a destination in the tourism sector. The aim of this study is to compare how the indicators of accessibility and connectivity of transportation have evolved across Spain's Autonomous Regions. To achieve this, we used indicators related to the sufficiency and connectivity of air and high-speed train services, as well as land accessibility and connectivity, as provided by Exceltur's Monitur reports. For a dynamic analysis, which is essential in assessing this type of infrastructure, we considered the values of these indicators from the first Monitur report (2010) and the most recent one (2018). Based on these values for the 17 Autonomous Regions of Spain, we identified the regions that have gained relative competitiveness and those that have experienced a relative decline. The dynamic analysis conducted in this study has allowed us to classify the regions according to the evolution of their relative competitiveness. It highlights the key areas that destination managers should focus on to design strategies that enhance their competitive position.

Estimating industry conduct using promotion data

AbstractWe estimate the evolution of competition in the ready‐to‐eat cereal industry. To separately identify detailed patterns of industry conduct from unobserved marginal cost shocks, we construct novel instruments that interact data on rival firms' promotions with measures of products' relative isolation in the characteristics space. We find strong evidence for partial price coordination among cereal manufacturers in the beginning of our sample. After a merger in 1993 conduct becomes more competitive and on average consistent with multiproduct Nash pricing. The last part of our sample is characterized by even more aggressive pricing, implying median wholesale margins of less than 5%.

Heterogeneous beliefs and short selling taxes: A note

Short selling is widespread in financial markets but regulators can ban short positions. The intermediate policy of taxing short sellers has been studied in an asset pricing model with evolutionary competition of two belief types (Anufriev and Tuinstra, 2013). We extend this approach to an arbitrary number of belief types H, giving 3H−2H cases to check each period in the worst-case scenario. We provide analytic expressions for asset prices along with conditions on beliefs (optimism) that determine which types take long, short or zero asset positions at the market-clearing price. We use these results to construct a fast solution algorithm (quadratic in H) which can solve models with hundreds or thousands of types in a matter of seconds. A numerical example with a short-selling tax and many heterogeneous beliefs in evolutionary competition shows that price dynamics can differ substantially relative to the benchmark of few types.

Social media marketing and performance of youth owned SMES in Nairobi County, Kenya

Fast technological evolution and intensity of competition oblige companies to constantly seek for new ways to differentiate and offer added value to their customers. With the increasing popularity of social media, companies have started to consider this means as a new way to communicate with their customers and increase their brand reputation. One of the most notable phenomena of new media is how it has increased and created new forms of social interaction.In Kenya, despite the critical role played by the Small and Medium Enterprises (SMEs) in the country, research has shown that 90% business startups fail in their third year and especially those owned by the youths The general purpose of the study was to establish the influence of social media marketing on performance of small and medium businesses in Nairobi’s industrial area. This study adopted a descriptive research design. Official records of AGPO as at December 2023 showed that there are 13,011 youth-owned businesses registered in the county of Nairobi with the Youth Access to Government Procurement Opportunities Program (YAGPO). The study used the 10-30% Mugenda Sampling principle to calculate the sample size of 130 SMEs. The first specific objective was to establish the extent Social Media Platforms Influence the Performance of Small and Medium Enterprises. A Pearson correlation analysis was done to establish the relationship between social media platform on performance of SMEs and the result established a significant positive relationship between social media platform used and the performance of SMEs (r=.811, p value =0.000). The second specific objective was to establish the extent bloggers influence the performance of Small and Medium Enterprises. A Pearson correlation analysis was done to establish the relationship between blogger influence on performance of SMEs and the result established a significant positive relationship between blogger influence and the performance of SMEs (r=.730, p value =0.000). The third objective was to establish the extent social media messaging factors influence the performance of Small and Medium Enterprises. A Pearson correlation analysis was done to establish the relationship between messaging factors on performance of SMEs and the result established a significant positive relationship between social media messaging factors used and the performance of SMEs (r=.359, p value =0.000). The study concluded that use of social media marketing has a positive influence on performance of SMEs and recommended that there is need for SMEs to embrace the use of social media to market their products and that the government should support SMEs by providing affordable internet services.

Clustering-based evolutionary algorithm for constrained multimodal multi-objective optimization

Handling constrained multimodal multi-objective optimization problems (CMMOPs) is a tremendous challenge as it involves the discovery of multiple equivalent constrained Pareto sets (CPSs) with the identical constrained Pareto front (CPF). However, the existing constrained multi-objective evolutionary algorithms are rarely suitable for solving CMMOPs due to the fact that they focus solely on locating CPF and do not intend to search for multiple equivalent CPSs. To address this issue, this paper proposes a framework of clustering-based constrained multimodal multi-objective evolutionary algorithm, termed FCCMMEA. In the proposed FCCMMEA, we adopt a clustering method to separate the population into multiple subpopulations for locating diverse CPSs and maintaining population diversity. Subsequently, each subpopulation evolves independently to produce offspring by an evolutionary algorithm. To balance the convergence and feasibility, we develop a quality evaluation metric in the classification strategy that considers the local convergence quality and constraint violation values, and it divides the populations into superior and inferior populations according to the quality evaluation of individuals. Furthermore, we also employ a diversity maintenance methodology in environmental selection to maintain the diverse population. The proposed FCCMMEA algorithm is compared with seven state-of-the-art competing algorithms on a standard CMMOP test suite, and the experimental results validate that the proposed FCCMMEA enables to find multiple CPSs and is suitable for handling CMMOPs. Also, the proposed FCCMMEA won the first place in the 2023 IEEE Congress on Evolutionary Computation competition on CMMOPs.

Trend analysis and regulatory strategies for traditional Chinese medicine formula granules

With the advent of the "post-pilot era" of traditional Chinese medicine formula granules, there are still a series of policy, technical, and industrial issues that need to be addressed in their production, regulation, and application practices. This article systematically reviews the development history and relevant policy evolution of traditional Chinese medicine formula granules, and summarizes the current industrial status in terms of quality standards, medical insurance payments, and market landscape. Based on a comparative analysis and positioning discussion between traditional Chinese medicine formula granules and traditional herbal decoctions, it is believed that the following practical issues still exist in this field:(1)A reasonable competitive evolution mechanism has not yet been formed, making it difficult to "improve quality and efficiency" of products;(2)The number of national standards is limited, and local standards operate independently;(3)Production processes are relatively constrained;(4)There is a contradiction between fixed equivalents and fluctuations in raw materials;(5)Market positioning needs to be clarified, and medication scenarios are limited. Furthermore, based on the perspective of shaping a healthy ecosystem for the traditional Chinese medicine industry and promoting rational clinical use of traditional Chinese medicine, the following suggestions are put forward:(1)Guide the formation of a product-based competitive landscape for traditional Chinese medicine formula granules;(2)Promote the establishment of a comprehensive regulatory system for the entire production process of traditional Chinese medicine formula granules;(3)Conduct systematic research on the relationship between the equivalents and intake of formula granules;(4)Break through existing application scenarios and reasonably expand the application forms of formula granules.

The evolution of competition and efficiency in U.S. Banking: new results from a novel two-step nonparametric method

ABSTRACT We examine the evolution of competition and efficiency in the U.S. banking industry over the past two decades by employing a novel two-step nonparametric method to estimate cost efficiency and the Lerner index for banks with multiple outputs. In the first step, data envelopment analysis is used to estimate the cost efficiency and the cost frontier. In the second step, the nonparametric local linear method is employed to smooth the estimated cost frontier, obtaining estimates of the marginal cost for each output and the Lerner index for each bank. Our innovative two-step nonparametric method has shed light on the evolving landscape of competition and efficiency that the ongoing consolidation in the U.S. banking sector is accompanied with the increasing trend of the concentration and the decreasing trend of efficiency. Further, small banks are more willing to set prices above their marginal costs but may not gain as much profit from a cost efficiency perspective. This phenomenon is a long-standing and enduring characteristic of the U.S. banking industry, reflecting the diverse strategies and priorities of banks operating in different market contexts.

Cooperative competition between melt-phase and void during micro-spallation and recompression

Dynamic tensile (micro-spallation) fracture and subsequent recompression in a molten state is the key physical process for metallic materials undergoing multiple intense dynamic loadings. However, there still lacks in-depth analysis of the complete evolution process from damage accumulation to recompression, as well as the influence of damage history on subsequent deformation and fracture. In the present work, the mechanism of cooperative competition evolution between the melt-phase and voids has been proposed as a new perspective to investigate damage evolution. Various important physical phenomena discovered in larger-scale MD simulations of molten aluminum can be self-consistently explained according to the proposed mechanism, such as the rate-dependence of spall strength and the pressure oscillation. The recompression-after-damage and second fracture process are discussed in detail to analyze the damage history effect. Under the present framework, two theoretical models have been proposed from the perspective of void and melt-phase evolution, respectively. The proposed models agree well with the simulation results and provide a comprehensive understanding of the damage evolutionary characteristics.

Evolutionary Competition Multitasking Optimization with Online Resource Allocation for Endmemeber Extraction of Hyperspectral Images

Hyperspectral remote sensing images typically have mixed rather than pure pixels. Endmember extraction aims to find a group of endmembers to represent the original image. In fact, the amount of endmembers is not easily determined in the existing endmember extraction studies.It requires several separate and laborious runs in order to produce results for endmember extraction with varying numbers of endmembers. There is also a correlation between the individual runs, which should be taken into account to accelerate algorithm convergence and improve accuracy. In this paper, an evolutionary competition multitasking optimization method (CMTEE) is proposed to achieve endmember extraction. In the proposed method, endmember extraction problems with different numbers of endmembers are considered as a group of optimization tasks. Specially, these tasks are assumed to be competitive. Then, online resource allocation is employed to assign suitable computational resources to the considered tasks. Experiments on simulated and real hyperspectral datasets demonstrated the effectiveness of the proposed evolutionary competition multitasking optimization method for endmember extraction.

Open Problems and Conjectures in the Evolutionary Periodic Ricker Competition Model

In this paper, we present a survey about the latest results in global stability concerning the discrete-time evolutionary Ricker competition model with n species, in both, autonomous and periodic models. The main purpose is to convey some arguments and new ideas concerning the techniques for showing global asymptotic stability of fixed points or periodic cycles in these kind of discrete-time models. In order to achieve this, some open problems and conjectures related to the evolutionary Ricker competition model are presented, which may be a starting point to study global stability, not only in other competition models, but in predator–prey models and Leslie–Gower-type models as well.

Trends and Paradoxes of Competitive Evolution in the Predation Mechanism

We give a series of numerical examples of competitive evolution in the predation system, showing in some cases how the choice is made to increase the efficiency of the predation mechanism (or other significant parameters) to the detriment of populations (both of prey and predators). We then develop the mathematical theory that enables us to understand the causality involved, and we identify a trend towards the emergence of the functional predation mechanism as such (and not of populations of the species involved). The realization of this trend only takes place when the conditions for it are offered by the hazards proposed to successive competitive choices. The logical structure of this trend is similar to that of the “tendency of rate of profit to fall” in certain economic models.

Examining Market Competition and Financial Stability: An Econometric Analysis of India’s Life and Non-Life Insurance Industry

Using the panel data analysis, this study investigates the evolution of competition over the study period and subsequently examines the relationship between competitiveness and financial stability within the Indian insurance segment. Adopting the methodology proposed by Boone (2008), competition is measured using the Boone indicator, while financial stability is quantified using the Z-score. Spanning over 15 years, i.e., 2009 to 2023, the study assesses both the life and non-life insurance segments within the Indian market. Throughout the study period, a decline in competition is observed across both segments, owing to the increased concentration among major insurers. Nevertheless, the study’s results support the Boyd and De Nicolo (2005) competition-stability hypothesis, suggesting that which suggests that increased market competition is associated with increased financial resilience. Additionally, the results using the Boone indicator highlight efficiency as the main mechanism by which competition fosters better financial stability. With their insights into the dynamics of competition and stability within the Indian insurance landscape, these findings have important ramifications for insurance companies, academics, and policymakers alike.

Evolutionary Competition in Small-Size Lowest Unique Integer Games

In lowest unique integer games (LUIGs), continually choosing the same number has been experimentally and computationally shown to be effective. However, this result holds only when all players behave differently, and it is unclear whether such behavior performs well under population dynamics. This study analyzed the types of agents that survive and how successfully they behave within an evolutionary environment of small-size LUIGs. Here, the author identified a learning model to create agents using behavioral data obtained from a laboratory experiment by Yamada and Hanaki. Then, evolutionary competition was pursued. The main findings are three fold. First, more agents are ruled out in three-person LUIGs than in four-person LUIGs. Second, the most successful agents do not win as much as the generations increase. Instead, they manage to win by adaptively changing their strategies. Third, as the scale of the LUIG increases, the number of wins for each agent is not correlated with that in a round-robin contest.

Calculation of Urban Green Competitiveness and Analysis of Spatial and Temporal Evolution Characteristics in China

It is particularly important to analyze the influencing factors of urban green competitiveness and the spatial distribution characteristics under the constraint of carbon emissions. The research ideas of this paper: firstly, this paper selects the carbon emission intensity and urban green competitiveness data in 2010, 2013, 2015, 2018 and 2020 for panel data regression; secondly, this paper applies a variety of methods to carry out the robustness test, and the results show that the regression model is better, and analyzes the development of urban green competitiveness for the heterogeneity of large cities and small cities; subsequently, the use of inverse geographic matrix to analyze the spatial correlation between the global Moran index and local Moran index for urban green competitiveness, and to analyze the spatial and temporal pattern evolution of urban green competitiveness. The conclusions of the study show that, from the viewpoint of influencing factors, carbon emission intensity presents a significant negative effect on the development of urban green competitiveness, and has a greater impact on the green competitiveness of large cities than that of small cities. From the perspective of spatial correlation, urban green competitiveness presents positive spatial correlation and shows a growing trend over time. Finally, this paper puts forward relevant policy recommendations based on the findings of the study.

The impact of consumer preferences on the evolution of competition in China's automobile market under the Dual Credit Policy-A density game based perspective.

The evolution of the automobile market is a macro-expression of the behavior of automakers' production decisions. This study examines the competitive environment between new energy vehicles (NEVs) and conventional fuel vehicles (CFVs) and develops a game-theoretical model incorporating consumer utility, automaker profit, and the competitive density of NEVs and CFVs. It aims to assess how consumers' preferences for vehicle range and smart features influence automakers' strategic decisions and the broader market evolution under the Dual Credit Policy. The findings indicate: (1) A low NEV credit price facilitates NEV market size growth, but this growth rate diminishes beyond a certain price threshold; (2) The lower the consumer's range preference, the higher NEV credit price can accelerate the development of new energy vehicles to their saturation value. However, when consumers in the market prioritize smart features, increasing the NEV credit price does not significantly influence the growth of NEV market size. (3) Higher consumer preferences for both range and smart features, combined with increased NEV credit prices, can synergistically accelerate the speed of the NEV market to reach the saturation value and also raise the saturation value of the scale of NEVs. And higher consumer range preference combined with increased NEV credit prices has a more significant effect on the promotion of NEV market size than the combined effect of higher consumer smart preference and increased NEV credit prices. The actual data of China's automobile market is used in the simulation of this model. The model and its simulation results effectively explain and reveal the evolutionary impacts of consumers' range and smart feature preference on the promotion of China's NEVs under the Dual Credit Policy to provide effective technological and theoretical support for the promotion of the sustainable development of China's NEV industry.

Differences in growth and competition between plants of a naturalized and an invasive population of Bunias orientalis.

The global shift of species' distributions has led to high numbers of noninvasive naturalized plants and the accumulation of invasive species within ecosystems. Competition between species may influence population dynamics, but little is known about the impacts of competition between conspecifics of naturalized and invasive populations. We investigated several plant traits at initial growth and regrowth following artificial defoliation in intra and interpopulation competition. Therefore, we used plants of Bunias orientalis from one noninvasive naturalized and one invasive population grown alone or in competition of two or three. Plants from the naturalized population were expected to be less competitive than plants from the invasive population, reflecting their differential impact in the introduced range. Independent of status, intrapopulation competition was expected to have less negative impacts on plants than interpopulation competition. Our results show that competition impacted mostly growth- rather than physiology-related traits. The relative magnitude of intra and interpopulation competition differed among plant traits at the first and second harvest. Plants of the invasive population outperformed the naturalized population by allocating relatively more resources to the aboveground biomass and producing more and longer leaves particularly when grown in competition against two plants. Moreover, plants of the invasive population were more competitive, which may influence their successful establishment and range expansion in the introduced range, but growth patterns differed after artificial defoliation. Although evolution of intrapopulation competition in naturalized and invasive ranges may be expected, interpopulation competition seems to adversely impact the performance of the naturalized plant population of B. orientalis studied here. Apart from the status (naturalized vs. invasive), other factors may have had an influence on plant performance. Thus, further research is needed with more naturalized and invasive populations to test the generality of our findings and to isolate the specific mechanisms driving differences in competitiveness.

Imitation Dynamics in Oligopoly Games with Heterogeneous Players

We investigate the role and performance of imitative behavior in a class of quantity-setting, Cournot games. Within a framework of evolutionary competition between rational, myopic best-response and imitation heuristics with differential heuristics’ costs, we found that the equilibrium stability depends on the sign of the cost differential between the unstable heuristic (Cournot best-response) and the stable one (imitation) and on the intensity of the evolutionary pressure. When this cost differential is positive (i.e., imitation is relatively cheaper vis a vis Cournot), most firms use this heuristic and the Cournot equilibrium is stabilized for market sizes for which it was unstable under Cournot homogeneous learning. However, as the number of firms increases (n=7), instability eventually sets in. When the cost differential is negative (imitation is more expensive than Cournot), complicated quantity fluctuations, along with the co-existence of heuristics, arise already for the triopoly game.

Winner-takes-all or competitive coexistence? Research on the co-opetition relationships between platform owners and complementors

PurposeThe purpose of this study is to explore the coopetition relationships between platform owners and complementors in complementary product markets. Drawing on the coopetition theory, the authors examined the evolutionary trends of the coopetition relationships between platform owners and complementors and explore the main influence factors.Design/methodology/approachThe authors used Lotka–Volterra model to analyze the coopetition relationship between platform owners and complementors, including the evolutionary trends as well as the results. Considering the feasibility of sample data collection, simulation is used to verify the effects of different factors on the evolution of coopetition relationships.FindingsThe results show that there are four possible results of the competition in the complementary products market. That comprises “winner-take-all for platform owners,” “winner-take-all for complementors,” “stable competitive coexistence” and “unstable competitive coexistence,” where “stable competitive coexistence” is the optimal evolutionary state. Moreover, the results of competitive evolution are determined by innovation subjects’ interaction parameters. However, the natural growth rate, the initial market benefits of the two innovators and the overall benefits of the complementary product markets influence the time to reach a steady state.Originality/valueThe study provides new insights into the entry of platform owners into complementary markets, and the findings highlight the fact that in complementary product markets, platform owners and complementors should seek “competitive coexistence” rather than “winner-takes-all.” Moreover, the authors also enrich the coopetition theory by revealing the core factors that influence the evolution of coopetition relationships, which further enhance the analysis of the evolutionary process of coopetition relationships.

Solving heterogeneous-belief asset pricing models with short-selling constraints and many agents

AbstractShort-selling constraints are common in financial markets, while physical assets such as housing often lack markets for short-selling altogether. As a result, investment decisions are often restricted by such constraints. This paper studies asset prices in behavioral heterogeneous-belief models with short-selling constraints and arbitrarily many belief types. We provide conditions on beliefs such that short-selling constraints bind for different types, along with analytic expressions for price and demands that allow us to construct fast solution algorithms relevant for a wide range of models. An application studies how an alternative uptick rule, as in the United States, affects price dynamics and wealth distribution in a market with many belief types in evolutionary competition. In a numerical example, we highlight a scenario in which a modified version of the alternative uptick rule, triggered by smaller percentage falls in price, reduces both asset mispricing and wealth inequality relative to the current regulation. As extensions, we show how our method applies to multiple asset markets with short-selling constraints, additional heterogeneities, and price setting by a market maker.