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Titlebook: Applications of Evolutionary Computation; 27th European Confer Stephen Smith,Jo?o Correia,Christian Cintrano Conference proceedings 2024 Th

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樓主: Orthosis
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發(fā)表于 2025-3-30 09:51:38 | 只看該作者
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發(fā)表于 2025-3-30 14:42:24 | 只看該作者
Evolutionary Feature-Binning with?Adaptive Burden Thresholding for?Biomedical Risk Stratification in statistical and machine-learning analyses. These relationships can limit the detection capabilities of many analytical methodologies when predicting outcomes including risk stratification in biomedical survival analyses. Feature Inclusion Bin Evolver for Risk Stratification (FIBERS) was previous
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發(fā)表于 2025-3-31 06:41:13 | 只看該作者
Hindsight Experience Replay with?Evolutionary Decision Trees for?Curriculum Goal Generationing the Grammatical Evolution algorithm. In the training stage, curriculum goals are then sampled by DTs to help the agent navigate the environment. Since binary DTs generate discrete values, we fine-tune these curriculum points by incorporating a feedback value (i.e., the .-value). This fine-tuning
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發(fā)表于 2025-3-31 09:50:31 | 只看該作者
Evolving Reservoirs for?Meta Reinforcement Learningehavioral policy through Reinforcement Learning (RL). Within an RL agent, a reservoir encodes the environment state before providing it to an action policy. We evaluate our approach on several 2D and 3D simulated environments. Our results show that the evolution of reservoirs can improve the learnin
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發(fā)表于 2025-3-31 14:22:21 | 只看該作者
Hybrid Surrogate Assisted Evolutionary Multiobjective Reinforcement Learning for?Continuous Robot Co parameter space of the policies that approximate the return of policies. An MOEA is executed that utilizes the surrogates’ mean prediction and uncertainty in the prediction to find approximate optimal policies. The final solution policies are later evaluated using the simulator and stored in an arc
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發(fā)表于 2025-3-31 19:34:49 | 只看該作者
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