This chapter explores the integration of symbolic reasoning and machine learning within the field of Neuro-Symbolic AI, a significant advancement in artificial intelligence. We investigate various reasoning methods, including deductive, inductive, abductive, analogical, probabilistic, common sense, and ...
d’Avila Garcez AS, Besold T, de Raedt L, Földiák P, Hitzler P, Icard T, Kühnberger K, Lamb LC, Miikkulainen R, Silver D (2015) Neural-symbolic learning and reasoning: Contributions and challenges. In: AAAI Spring Symposia.http://www.aaai.org/ocs/index.php/SSS/SSS15/paper/vi...
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This chapter explores the integration of symbolic reasoning and machine learning within the field of Neuro-Symbolic AI, a significant advancement in artificial intelligence. We investigate various reasoning methods, including deductive, inductive, abductive, analogical, probabilistic, common sense, and combin...
Compositional Attention Networks for Machine Reasoning 发表会议:ICLR 2018 论文链接:openreview.net/pdf? 这篇文章提出了MACnet模型去解决VQA任务。MAC,即Memory,Attention,Composition。MACnet是MAC cell的soft-attention序列。一个Mac cell由控制单元、读单元、写单元构成,如图5所示。
摘要: Human–Machine Interaction (HMI) interfaces have predominantly relied on GUI and voice commands. However, natural human communication also consists of non-verbal communication, ...关键词: Human–machine interaction Referring expression comprehension Neuro-symbolic reasoning Multimodal learning ...
improvements (e.g., scene graph generation) rather than reasoning.Neuro-symbolic modelssuch as Neural Module Networks bring the benefits of compositional reasoning to VQA, but they are still entangled with visual representation learning, and thus neural reasoning is hard to improve...
Neither deep neural networks nor symbolic artificial intelligence (AI) alone has approached the kind of intelligence expressed in humans. This is mainly because neural networks are not able to decompose joint representations to obtain distinct objects (t
A neuro-symbolic reasoning strategy for modelling a complex system is presented in which the aim is to forecast, in real time, the physical parameter values of a dynamic environment: the ocean. In situations in which the rules that determine a system are unknown the prediction of the parameter...
Garcez Ad, Lamb LC (2023) Neurosymbolic ai: the 3rd wave. Artif Intell Rev 56:1–20 Google Scholar Towell GG, Shavlik JW (1994) Knowledge-based artificial neural networks. Artif intell 70(1–2):119–165 Google Scholar Pinkas G (1995) Reasoning, nonmonotonicity and learning in connectio...