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Fuzzy logic and fuzzy systems: recent developments and future directions

机译:模糊逻辑和模糊系统:最近的发展和未来方向

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Over the last decade or so, several parallel advances have been made in the two distinct disciplines: fuzzy logic and neural networks. As the names imply, the theory of fuzzy logic provides a mathematical framework for the emulation of certain perceptual and linguistic attributes associated with human cognition, whereas the science of neural networks provides new computing morphologies with learning and adaptive capabilities. A marriage between these two distinct disciplines has the potential of producing robotic machines with some sort of cognitive abilities. We briefly examine these two fields: fuzzy logic and neural networks, and explore the possibilities of their integration in the development of cognitive robotic systems.
机译:在过去十年左右,两种不同的学科已经进行了几个平行的进步:模糊逻辑和神经网络。由于名称暗示,模糊逻辑理论为模拟与人类认知相关的某些感知和语言属性的仿真提供了数学框架,而神经网络的科学提供了新的计算形态,具有学习和自适应能力。这两个不同的学科之间的婚姻具有产生具有某种认知能力的机器人机的潜力。我们简要仔细检查了这两个领域:模糊逻辑和神经网络,并探讨了他们在认知机器人系统发展中融入的可能性。

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