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Fikes, R., & Garvey, T. (2020). Knowledge representation and reasoning--a history of darpa leadership. AI Magazine, 41(2). 
Resource type: Journal Article
BibTeX citation key: Fikes2020
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Categories: Artificial Intelligence, Cognitive Science, Computer Science, Data Sciences, Decision Theory, General, Military Science, Neuroscience
Subcategories: Autonomous systems, Deep learning, Human decisionmaking, Human learning, Machine intelligence, Machine learning, Machine recognition, Neurosymbolic, Synthetic intelligence
Creators: Fikes, Garvey
Publisher:
Collection: AI Magazine
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Abstract
A fundamental goal of artificial intelligence research and development is the creation of machines that demonstrate what humans consider to be intelligent behavior. Effective knowledge representation and reasoning methods are a foundational requirement for intelligent machines. The development of these methods remains a rich and active area of artificial intelligence research in which advances have been motivated by many factors, including interest in new challenge problems, interest in more complex domains, shortcomings of current methods, improved computational support, increases in requirements to interact effectively with humans, and ongoing funding from the Defense Advanced Research Projects Agency and other agencies. This article highlights several decades of advances in knowledge representation and reasoning methods, paying particular attention to research on planning and on the impact of the Defense Advanced Research Projects Agency's support.
  
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