GPS, a program that simulates human thought

By Allen Newell, Herbert A. Simon. 1995

How researchers see this paper

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Citations in the corpus

Optimal Ordered Problem Solver (2002, neutral): “Since the early attempts of Newell and Simon (1963) at building a “General Problem Solver” —see also Rosenbloom et al. (1993)—much work has been done to develop mostly heuristic machine learning algorithms that solve new problems based on experience with previous problems, by incrementally shifting…”
Planning algorithms (2006, background): “Throughout the history of artificial intelligence research, the distinction between problem solving [738] and planning has been rather elusive.”
On Fast Deep Nets for AGI Vision (2011, background): “The ﬁrst decades of attempts at AGI have been dominated by heuristic approaches, e.g., [15, 16, 26, 14].”
The Fast Downward Planning System (2006, methodology): “The approach of hierarchically decomposing planning tasks is arguably as old as the field of AI Planning itself, having first surfaced in Newell and Simon’s (1963) work on the General Problem Solver. Still, it took a long time for these notions to evolve to their modern form. Sacerdoti’s (1974) ABST”
On Defining Artificial Intelligence (2019, methodology): “In the AI projects he participated, GPS (Newell and Simon, 1963) and BACON (Simon, Langley, and Bradshaw, 1981), the restriction of knowledge and resources was taken into consideration in certain aspects (such as using heuristics to get satisficing solutions), but not in the sense of AIKR.”
Children's understanding of representational change and its relation to the understanding of false belief and the appearance-reality distinction. (1988, background): “Even machine learning systems must be able to represent their past representational states and retrace the path that led them to those states in order to modify their learning strategies (Newell & Simon, 1963).”
Learning Networks and Connective Knowledge (2010, result): “The ‘General Problem Solver’ of Newell and Simon (1963) , for example, take a ‘symbol processing’ approach to computation in AI. This is similar to the Fodor theory, the idea that cognition is (essentially) reducible to a physical symbol set (and therefore instances of cognition and transaction) ar”
A Roadmap of Agent Research and Development (2004, background): “The AI planning paradigm traces its origins to Newell and Simon’sgps system [108], but is most commonly associated with the strips planning system ( [45]) and its descendents (such as [23, 156]).”
Automated Planning and Acting (2016, methodology): “This began with the early work on GPS [451] and the situation calculus [413] and continued with the STRIPS planning system [197] and the widely used classical18 representations [460, 472, 384, 231, 517].”