The logic theory machine-A complex information processing system

By Allen Newell, Herbert A. Simon. 1956

Subfields: Knowledge Graphs & Representation

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Citations in the corpus

Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge (2020, background): “Knowledge bases (KBs) have been a core component of AI since the beginning of the field (Newell and Simon, 1956; Newell et al., 1959).”
PRover: Proof Generation for Interpretable Reasoning over Rules (2020, background): “Developing systems that can understand and reason over explicitly provided knowledge has been a fundamental goal of AI (Newell and Simon, 1956).”
Probabilistic models of cognition: exploring representations and inductive biases. (2010, unknown): “[2] to the most successful contemporary paradigms [3], have started with computational”
GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models (2024, unknown): “Logical reasoning is a critical trait of intelligent systems, and building intelligent systems capable of such reasoning has long been an important goal in artificial intelligence (Newell & Simon, 1956; Marcus, 2003; Brachman & Levesque, 2004; Legg & Hutter, 2007; Pearl, 2014; Chollet, 2019).”
Genetic Programming: An Introduction (1997, background): “) Newell and Simon (1977) have described the traditional AI paradigm in terms of goal-directed problem solving.”
Tunneling Neural Perception and Logic Reasoning through Abductive Learning (2018, background): “In this branch of AI research, a series of important steps has been achieved, e.g., automatic theorem proving [33, 5], propositional rule learning [9], expert systems [18], automated planning [8] and inductive logic programming [31], and so on.”
History of Interactive Theorem Proving (2014, methodology): “It is true that there was still a considerable diversity of methods, with some researchers pursuing AI-style approaches [Newell and Simon, 1956; Gelerntner, 1959; Bledsoe, 1984] rather than the dominant theme of automated proof search, and that the proof search programs were often highly tunable by…”
Working memory, attention and their relationship: A theoretical overview (2021, background): “…to create a computer problem-solving program, the logic theory machine, they designed working memories, namely computer memories for temporary information retention that differed from storage memories, that is, memories for permanent information storage (Logie & Cowan, 2015; Newell & Simon, 1956).”
A Review on Language Models as Knowledge Bases (2022, background): “It has been a long-standing goal of AI to reason over explicit knowledge given to it in order to reach conclusions (McCarthy, 1959; Newell and Simon, 1956; Metaxiotis et al., 2002).”
Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding (2021, background): “Building large-scale repositories of knowledge has been one of the principle directions of research in artificial intelligence since the inception of the field (Newell and Simon, 1956; Newell et al., 1959).”
The Cognitive Perspective in Entrepreneurship: An Agenda for Future Research (2011, unknown): “This process orientation is perhaps most commonly associated with the informationprocessing model (cf. Broadbent, 1958; Neisser, 1967; Newell and Simon, 1956) and the so-called ‘computational perspective’ on human behaviour (cf. Anderson, 1983; Lant and Shapira, 2001).”
Studies of Expertise from Psychological Perspectives (2006, background): “The Logic Theorist (LT) was coded in IPL.”
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations (2021, background): “While KBs have been a key component of artificial intelligence since the field’s inception (Newell & Simon, 1956; Newell et al., 1959) broad-coverage KBs are inevitably incomplete (Min et al., 2013), despite efforts to automate their creation through text extraction (Angeli et al., 2015; Mitchell…”
When immediate interactive feedback boosts optimization problem solving: A 'human-in-the-loop' approach for solving Capacitated Vehicle Routing Problems (2017, methodology): “This comes in alignment with Simon’s position (Newell & Simon, 1956) where solvers perform a serial search of item-by-item and they finish it as soon as they find a ‘satisficing’ utility.”