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Gradient-Based Competitive Learning: Theory
Deep learning has been recently used to extract the relevant features for representing input data also in the unsupervised setting. However,...
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Mixed effects of cooperative/competitive gamification on language learning regarding engagement, foreign language enjoyment, and classroom social climate
This study reflects how gamification with cooperation/competition mechanics enhances language learning regarding engagement, foreign language...
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Leveraging transfer learning in reinforcement learning to tackle competitive influence maximization
Competitive influence maximization (CIM) is a key problem that seeks highly influential users to maximize the party’s reward than the competitor....
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A competitive learning-based Grey wolf Optimizer for engineering problems and its application to multi-layer perceptron training
This article presents a competitive learning-based Grey Wolf Optimizer (Clb-GWO) formulated through the introduction of competitive learning...
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Towards a Competitive Two-Player Anti-phishing Learning Game
This paper explores the design and implementation of a competitive two-player anti-phishing learning game on the topic of phishing emails, aiming to...
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Cumulative learning-based competitive swarm optimizer for large-scale optimization
Competitive swarm optimizer (CSO) has shown advantages for solving large-scale optimization. However, some major problems, such as low solution...
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Backdoor Attacks Leveraging Latent Representation in Competitive Learning
Backdoor attacks on machine learning are attacks where an adversary obtains the expected output for a particular input called a trigger, and a...
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Competitive Collaboration for Complex Task Learning in Agent Systems
This paper presents a novel competitive collaboration-based reinforcement learning strategy to improve the performance of goal-oriented autonomous...
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Incorporating rivalry in reinforcement learning for a competitive game
Recent advances in reinforcement learning with social agents have allowed such models to achieve human-level performance on certain interaction...
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Bias Estimation Correction in Multi-Agent Reinforcement Learning for Mixed Cooperative-Competitive Environments
Multi-agent reinforcement learning (MARL) is a domain that is being actively researched in the current times. The ability of MARL algorithms in...
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Competitive Programming Vestige Using Machine Learning
Competitive programming improves our problem-solving abil ity. It helps in writing the source code of computer programs that help in solving given...
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Online teacher developmental feedback in competitive environments: the moderation roles of timeliness and regulatory focus
Under the tenet of framing and regulatory theory, this study undertakes a comprehensive examination of the impacts of task-oriented and self-oriented...
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An Improved Competitive Swarm Optimizer with Super-Particle-Leading
Competitive swarm optimizer (CSO) has been concerned in recent years due to its achievements in solving global optimization problems. However, the...
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The rapid competitive economy of machine learning development: a discussion on the social risks and benefits
Research in artificial intelligence (AI) has started in the twentieth century but it was not until 2012 that modern models of artificial neural...
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Toward competitive multi-agents in Polo game based on reinforcement learning
The learning of agents in a competitive space such as a game is a challenging task. The aim of the proposed research is to improve the reinforcement...
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Toward Explaining Competitive Success in League of Legends: A Machine Learning Analysis
Machine learning techniques have recently transformed the way we analyze competitive games. However, accurately detecting the impact of different...
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CLP: A Platform for Competitive Learning
We introduce the Competitive Learning Platform (CLP), an online continuous improvement tool that provides automatic partial performance feedback to...
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Competitive Learning and Dynamic Genetic Algorithms for Robust Layout Designs Under Uncertainties
Machine layout design is a crucial part of company’s operations and commonly aimed at maximising the effectiveness of resource utilisation within the...
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An investigation of the virtual competitive scaffolding assistant: a prior knowledge perspective
Virtual competition can address the problems of real competition, but there is a lack of sufficient interactive engagement. Furthermore, virtual...
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A Novel Continual Learning Approach for Competitive Neural Networks
Continual learning tries to address the stability-plasticity dilemma to avoid catastrophic forgetting when dealing with non-stationary distributions....