Semantic networks are a form of knowledge representation that depict relationships between concepts in a graphical format. Nodes in the network represent entities or concepts, while edges illustrate the relationships or associations between them. This structure allows for efficient organization and retrieval of information, making it useful in various applications such as natural language processing, information retrieval, and artificial intelligence. Semantic networks can model complex relationships and hierarchies, enabling machines to understand and infer meaning from interconnected data. They are particularly beneficial in tasks involving reasoning and knowledge representation.
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AI FundamentalsLearn about the SARSA algorithm, an on-policy reinforcement learning method for maximizing expected ...
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AI Fundamentals