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Evolution of Attraction for Cooperation
We are investigating an attraction mechanism that models interpersonal relations such that an individual acts differently, and presumably more...
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Optimization of large-scale UAV cluster confrontation game based on integrated evolution strategy
The development of large-scale cluster intelligence will inevitably lead to new problems of adversarial game control. Aiming at the problem of high...
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Reinforcement Learning-Based Differential Evolution Algorithm with Levy Flight
In this paper, a reinforcement learning-based differential evolution algorithm with levy flight strategy (RLLDE) for solving optimization problems is...
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Rolling Horizon Co-evolution for Snake AI Competition
The Snake game, a classic in the gaming world, gains new dimensions with the Snake AI competition, where two players controlled by AI algorithms can...
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Fuzzy Pattern Tree Evolution Using Grammatical Evolution
A novel approach to induce Fuzzy Pattern Trees using Grammatical Evolution is presented in this paper. This new method, called Fuzzy Grammatical...
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Sequential seeding policy on social influence maximization: a Q-learning-driven discrete differential evolution optimization
The influence maximization problem that has caused great attention in social network analysis aims at selecting a small set of influential spreaders...
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Resampling strategies for imbalanced regression: a survey and empirical analysis
Imbalanced problems can arise in different real-world situations, and to address this, certain strategies in the form of resampling or balancing...
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DEMFFA: a multi-strategy modified Fennec Fox algorithm with mixed improved differential evolutionary variation strategies
The Fennec Fox algorithm (FFA) is a new meta-heuristic algorithm that is primarily inspired by the Fennec fox's ability to dig and escape from wild...
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Comparison of Simulated Annealing and Evolution Strategies for Optimising Cyclical Rosters with Uneven Demand and Flexible Trainee Placement
Rosters are often used for real-world staff scheduling requirements. Multiple design factors such as demand variability, shift type placement, annual...
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Hypergraph Structure Evolution
In practice, noise exists in the process of data collection and hypergraph construction. Therefore, missing, abundant, and noisy connections may be...
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TDAE: Text Detection with Affinity Areas and Evolution Strategies
Text detection in natural scenes has evolved considerably in recent years. Segmentation-based methods are widely used for text detection because they...
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Navigating the Digital Landscape: Enhancing Service Discovery and Portability in Digital Marketing Strategies
In today's fast-paced digital landscape, businesses are compelled to embrace digital marketing strategies to reach and engage their target audiences...
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Strategy evolution on dynamic networks
Models of strategy evolution on static networks help us understand how population structure can promote the spread of traits like cooperation. One...
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Enhancing differential evolution algorithm with a fitness-distance-based selection strategy
Since the introduction of differential evolution (DE) algorithms, they have achieved remarkable success in the field of evolutionary algorithms and...
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Strategies for mitigating detrimental effects in cyber-physical multiplex networks
This study unveils two innovative mechanisms (EACM and ERSM) for mitigating detrimental items such as epidemics and rumors, both meticulously devised...
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Modeling and verification of software evolution using bigraphical reactive system
Changes are inevitable in software due to technology advancements, and changes in business requirements. Making changes in the software by insertion,...
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A Grammatical Evolution Based Automated Configuration of an Ensemble Differential Evolution Algorithm
Designing/configuring ensemble Differential Evolution (DE) algorithms with complementary search characteristics is a complex problem requiring both...
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Automatic Requirement Dependency Extraction Based on Integrated Active Learning Strategies
Since requirement dependency extraction is a cognitively challenging and error-prone task, this paper proposes an automatic requirement dependency...
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ADE: advanced differential evolution
This paper proposes a metaheuristic algorithm, called advanced differential evolution (ADE), by improving the DE algorithm. The ADE algorithm was...
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Evidential uncertainty sampling strategies for active learning
Recent studies in active learning, particularly in uncertainty sampling, have focused on the decomposition of model uncertainty into reducible and...
