Cooperative co-evolution of GA-based classifiers based on input increments

Genetic algorithms (GAs) have been widely used as soft computing techniques in various applications, while cooperative co-evolution algorithms were proposed in the literature to improve the performance of basic GAs. In this paper, a new cooperative co-evolution algorithm, namely ECCGA, is proposed in the application domain of pattern classification. Concurrent local and global evolution and conclusive global evolution are proposed to improve further the classification performance. Different approaches of ECCGA are evaluated on benchmark classification data sets, and the results show that ECCGA can achieve better performance than the cooperative co-evolution genetic algorithm and normal GA. Some analysis and discussions on ECCGA and possible improvement are also presented

A Descriptive Model of Robot Team and the Dynamic Evolution of Robot Team Cooperation

At present, the research on robot team cooperation is still in qualitative analysis phase and lacks the description model that can quantitatively describe the dynamical evolution of team cooperative relationships with constantly changeable task demand in Multi-robot field. First this paper whole and static describes organization model HWROM of robot team, then uses Markov course and Bayesian theorem for reference, dynamical describes the team cooperative relationships building. Finally from cooperative entity layer, ability layer and relative layer we research team formation and cooperative mechanism, and discuss how to optimize relative action sets during the evolution. The dynamic evolution model of robot team and cooperative relationships between robot teams proposed and described in this paper can not only generalize the robot team as a whole, but also depict the dynamic evolving process quantitatively. Users can also make the prediction of the cooperative relationship and the action of the robot team encountering new demands based on this model. Journal web page & a lot of robotic related papers www.ars-journal.co

Limited Evaluation Cooperative Co-evolutionary Differential Evolution for Large-scale Neuroevolution

Many real-world control and classification tasks involve a large number of features. When artificial neural networks (ANNs) are used for modeling these tasks, the network architectures tend to be large. Neuroevolution is an effective approach for optimizing ANNs; however, there are two bottlenecks that make their application challenging in case of high-dimensional networks using direct encoding. First, classic evolutionary algorithms tend not to scale well for searching large parameter spaces; second, the network evaluation over a large number of training instances is in general time-consuming. In this work, we propose an approach called the Limited Evaluation Cooperative Co-evolutionary Differential Evolution algorithm (LECCDE) to optimize high-dimensional ANNs. The proposed method aims to optimize the pre-synaptic weights of each post-synaptic neuron in different subpopulations using a Cooperative Co-evolutionary Differential Evolution algorithm, and employs a limited evaluation scheme where fitness evaluation is performed on a relatively small number of training instances based on fitness inheritance. We test LECCDE on three datasets with various sizes, and our results show that cooperative co-evolution significantly improves the test error comparing to standard Differential Evolution, while the limited evaluation scheme facilitates a significant reduction in computing time

Cooperative Evolution

Cooperative Evolution offers a fresh account of evolution consistent with Charles Darwin's own account of a cooperative, inter-connected, buzzing and ever-changing world. Told in accessible language, treating evolutionary change as a cooperative enterprise brings some surprising shifts from the traditional emphasis on the dominance of competition. The book covers many evolutionary changes reconsidered as cooperation. These include the cooperative origins of life, evolution as a spiral rather than a ladder or tree, humans as a part of natural systems rather than the purpose, relationships between natural and social change, and the role of the individual in adaptive radiation onto new ground. The story concludes with a projection of human evolution from the past into the future

Democratic corporate governance within fluctuating cooperative banks: A multidisciplinary diagnosis and proposition of orientations.

The democratic question became of an ardent actuality within cooperative banks since the end of the 1990's. Founding element of human-sized organizations that were the first mutual or cooperative Caisses, is democracy running the risk to dissolve by necessity in the mature and hybrid giants that are the big banking cooperative groups nowadays? The present article unveils a multidisciplinary synthesis made possible by the conjunction of three researchers studying cooperative banks through three complementary angles: law, economy and management. After a first inventory of the possible symptoms of the disappearance of democracy inherent to the cooperative project, a more differentiating diagnosis is proposed, followed by an outline of some working leads for a creative evolution of cooperative democracy.Democracy; bank;cooperative; pluridisciplinarity; new cooperative paradigm

Culture Outsmarts Nature in the Evolution of Cooperation

A one dimensional cellular automata model describes the evolutionary dynamics of cooperation when grouping by cooperators provides protection against predation. It is used to compare the dynamics of evolution of cooperation in three settings. G: only vertical transmission of information is allowed, as an analogy of genetic evolution with heredity; H: only horizontal information transfer is simulated, through diffusion of the majority\'s opinion, as an analogy of opinion dynamics or social learning; and C: analogy of cultural evolution, where information is transmitted both horizontally (H) and vertically (V) so that learned behavior can be transmitted to offspring. The results show that the prevalence of cooperative behavior depends on the costs and benefits of cooperation so that: a- cooperation becomes the dominant behavior, even in the presence of free-riders (i.e., non-cooperative obtaining benefits from the cooperation of others), under all scenarios, if the benefits of cooperation compensate for its cost; b- G is more susceptible to selection pressure than H achieving a closer adaptation to the fitness landscape; c- evolution of cooperative behavior in H is less sensitive to the cost of cooperation than in G; d- C achieves higher levels of cooperation than the other alternatives at low costs, whereas H does it at high costs. The results suggest that a synergy between H and V is elicited that makes the evolution of cooperation much more likely under cultural evolution than under the hereditary kind where only V is present.Social Simulation, Interactions, Group Size, Selfish Heard, Cultural Evolution, Biological Evolution

Evolution of Cooperative Thought, Theory, and Purpose

The evolution of agricultural cooperative thought, theory, and purpose in the United States is reviewed from the standpoint of the reemergence of interest in how cooperatives can provide some of the security and benefits that might be lost with gradual phasing out of federal government farm support programs. By accomplishing group action for self-help, the early development of cooperatives drew considerable attention from economists, social theorists, and politicians. Alternative schools of cooperative thought developed, but most proponents of cooperatives regarded them as having enormous potential to provide a public service role in building a more economically stable and democratic society This paper also surveys how cooperative theory was developed more rigorously in the post-WWII period. It has provided better analytical tools for understanding how and why cooperatives have changed in response to technological and economic developments, as well as to social trends, like individualism. Given the new perspectives on cooperative theory and the scope of changes in how cooperatives operate and are structured, cooperatives have even greater potential for coordinating self-help actions, but this potential needs the support of cooperative education services.Agribusiness,

The Evolution of Language Groups among Cooperating Digital Predators

Many species of animals have evolved complex means for communicating with one another. Oftentimes, communication is essential for the execution of tasks that require cooperation between individuals, such as group hunting and mate selection. As a result, communication itself becomes essential for survival. While these facts are readily observed, the evolutionary processes underlying them are less understood, in large part because observational - much less controlled - studies of these processes are impossible. Both the timescales and population sizes required for such studies are simply too great. To address these problems, this thesis uses simulated predators to study the evolution of language in animals. These digital predators evolve to perform two cooperative tasks: hunting and mate selection. After the populations of predators have evolved to perform both tasks successfully, the population is decomposed into both language groups and cooperative groups. Spectral clustering identifies predators that speak similar languages, while merge clustering is used to find those groups of predators that are the most successful when working together. Analysis of the groups generated by these two different methods shows that the most successful pairings are not necessarily those in which the two individuals are speaking the same language. Rather, organisms can evolve to speak a different language than the one to which they respond. Moreover, even though one task -- mate selection -- evolves earlier in evolutionary history, the language diversity it produces counteracts any head-start provided for the evolution of the second task. Thus, not only is language important for the evolution of cooperative task success, but the appearance of language groups can also play a determinant role in the evolution of cooperation.Computer Science