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The notion that beliefs, attitudes, and ideology were deeply connected knowledge structures was contained in Scripts, Plans, Goals, and Understanding (1977, with Roger Schank), a work that has collected several thousand citations, and led to the first interdisciplinary graduate program in cognitive science at Yale. His work on voting behavior ...
Roger Carl Schank (March 12, 1946 – January 29, 2023) was an American artificial intelligence theorist, cognitive psychologist, learning scientist, educational reformer, and entrepreneur. Beginning in the late 1960s, he pioneered conceptual dependency theory (within the context of natural language understanding ) and case-based reasoning ...
Roger Schank, Robert P. Abelson and their research group, extended Tomkins' scripts and used them in early artificial intelligence work as a method of representing procedural knowledge. [1] In their work, scripts are very much like frames, except the values that fill the slots must be ordered. A script is a structured representation describing ...
Roger Schank and Robert Abelson developed the idea of a script, which was known as a generic knowledge of sequences of actions. This led to many new empirical studies, which found that providing relevant schema can help improve comprehension and recall on passages. [25]
Much of the early Frame language research (e.g. Schank and Abelson) had been driven by findings from experimental psychology and attempts to design knowledge representation tools that corresponded to the patterns humans were thought to use to function in daily tasks.
Schank & Abelson (1977) described this inclusion of typical beliefs, desires, and intentions underlying an action as akin to a "script" whereby an individual is merely following an unconscious framework that leads to the ultimate decision of whether an action will be performed. [19]
The distinction between neat and scruffy originated in the mid-1970s, by Roger Schank.Schank used the terms to characterize the difference between his work on natural language processing (which represented commonsense knowledge in the form of large amorphous semantic networks) from the work of John McCarthy, Allen Newell, Herbert A. Simon, Robert Kowalski and others whose work was based on ...
Roger Schank at Stanford University introduced the model in 1969, in the early days of artificial intelligence. [1] This model was extensively used by Schank's students at Yale University such as Robert Wilensky, Wendy Lehnert, and Janet Kolodner. Schank developed the model to represent knowledge for natural language input into computers.