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Titlebook: Highlights on Practical Applications of Agents and Multi-Agent Systems; 10th International C Javier Bajo Pérez,Miguel A. Sánchez,Vicente Ju

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樓主: metabolism
21#
發(fā)表于 2025-3-25 06:52:51 | 只看該作者
José Barbosa,Paulo Leit?o,Emmanuel Adam,Damien Trentesaux brought artificial intelligence technology, which has once again risen in the past decade, to the stage and into the public view. In the past few years, technology giants have successively established artificial intelligence laboratories, invested more and more resources to capture the artificial i
22#
發(fā)表于 2025-3-25 10:41:02 | 只看該作者
23#
發(fā)表于 2025-3-25 13:07:38 | 只看該作者
24#
發(fā)表于 2025-3-25 17:20:44 | 只看該作者
25#
發(fā)表于 2025-3-25 23:53:55 | 只看該作者
26#
發(fā)表于 2025-3-26 01:52:51 | 只看該作者
Roussanka Loukanova,M. Dolores Jiménez-Lópezosing the optimal control parameters of DE is a time-consuming task because they are problem depended. DE may have a strong ability in exploring the search space and locating the promising area of global optimum but may be slow at exploitation. Thus, in this paper, we propose a Gaussian Cauchy diffe
27#
發(fā)表于 2025-3-26 05:02:51 | 只看該作者
28#
發(fā)表于 2025-3-26 11:28:12 | 只看該作者
Joel Azzopardi,Christopher Staffhms in large scale graph computing. The high time complexity, which even exceed that of the final algorithms occasionally, is the main factor to prevent their applicabilities. Existing graph partitioning algorithms are mostly based on multilevel k-way scheme or iterative label propagation. Most of t
29#
發(fā)表于 2025-3-26 13:41:57 | 只看該作者
30#
發(fā)表于 2025-3-26 16:49:52 | 只看該作者
A. Gil,S. Rodríguez,F. De la Prieta,B. Martín,M. Morenointelligence (AGI) in game playing. However, deep learning is resource-intensive and the theory is not yet well developed. For small games, simple classical table-based Q-learning might still be the algorithm of choice. General Game Playing (GGP) provides a good testbed for reinforcement learning to
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