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Artificial intelligence (AI) is the Science and Engineering domain concerned with the theory and practice of developing systems that exhibit the characteristics we associate with intelligence in human behavior. Starting with a brief history of artificial intelligence, this article presents a general overview of this broad interdisciplinary field, organized around the main modules of the notional architecture of an intelligent agent (knowledge representation; problem solving and planning; knowledge acquisition and learning; natural language, speech, and vision; action processing and robotics) which highlights both the main areas of artificial intelligence research, development and application, and also their integration. WIREs Comput Stat 2012, 4:168–180. doi: 10.1002/wics.200 This article is categorized under: Software for Computational Statistics > Artificial Intelligence and Expert Systems

Over the years we have developed the Disciple theory, methodology, and family of tools for building knowledge-based agents. This approach consists in developing an agent shell that can be taught directly by a subject matter expert, in a way that resembles how the expert would teach a human apprentice when solving problems in cooperation. This paper presents the most recent version of the Disciple approach and its implementation in the Disciple-RKF system. Disciple-RKF is based on methods for mixed-initiative problem solving, where the expert solves the more creative problems and the agent solves the more routine ones, integrated teaching and learning, where the agent helps the expert to teach it, by asking relevant questions, and the expert helps the agent to learn, by providing examples, hints and explanations, and multistrategy learning, where the agent integrates multiple learning strategies, such as learning from examples, learning from explanations, and learning by analogy, to learn from the expert how to solves problems.Disciple-RKF has been successfully applied to build learning and reasoning agents for military center of gravity analysis, which are used in several courses at the US Army War College.

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