Titlebook: Agents and Artificial Intelligence; 15th International C Ana Paula Rocha,Luc Steels,Jaap van den Herik Conference proceedings 2024 The Edit

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https://doi.org/10.1007/978-90-481-2554-8 replacement, and the need for upgrade scenarios occur. Our approach was evaluated and tested in three different BDI frameworks, demonstrating that swapping resources at runtime is a promissory feature to guarantee the adaptability of intelligent cyber-physical systems.

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https://doi.org/10.1007/978-94-015-7694-9ecasting models, a multivariate variant of the N-BEATS model (M-N-BEATS) and a hybrid Transformer-N-BEATS (TRANS-BEATS) model, both for multivariate multi-step ahead time-series forecasting. The proposed models outperform their rivals and their forecasting performance is evaluated by multiple evalua

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https://doi.org/10.1007/978-3-031-44995-6he claim that in some cases these more recent memory modules can improve the performance of the agent, to varying degrees, when compared to a baseline agent based on an LSTM. The experimental results were validated in the Atari 2600 videogame platform.

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https://doi.org/10.1007/978-1-349-07867-7ios. In our study, we employ seven distinct weight re-mapping functions to assess their impact on eight classification datasets, using variational classifiers as a representative example. Our results indicate that weight re-mapping can enhance the convergence speed of the VQC. We assess the efficacy

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