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pro vyhledávání: '"Ghaemi, Hafez"'
Autor:
Ghaemi, Hafez, Jamshidi, Shirin, Mashreghi, Mohammad, Ahmadabadi, Majid Nili, Kebriaei, Hamed
Markov games (MGs) and multi-agent reinforcement learning (MARL) are studied to model decision making in multi-agent systems. Traditionally, the objective in MG and MARL has been risk-neutral, i.e., agents are assumed to optimize a performance metric
Externí odkaz:
http://arxiv.org/abs/2406.06041
Classical multi-agent reinforcement learning (MARL) assumes risk neutrality and complete objectivity for agents. However, in settings where agents need to consider or model human economic or social preferences, a notion of risk must be incorporated i
Externí odkaz:
http://arxiv.org/abs/2402.05906
Publikováno v:
In Neurocomputing 28 December 2024 610
Brain-inspired computation and information processing alongside compatibility with neuromorphic hardware have made spiking neural networks (SNN) a promising method for solving learning tasks in machine learning (ML). Spiking neurons are only one of t
Externí odkaz:
http://arxiv.org/abs/2109.05539
A conventional brain-computer interface (BCI) requires a complete data gathering, training, and calibration phase for each user before it can be used. In recent years, a number of subject-independent (SI) BCIs have been developed. Many of these metho
Externí odkaz:
http://arxiv.org/abs/2012.13567
Publikováno v:
In Digital Signal Processing March 2023 133