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## General Problem Solver (A. Newell & H. Simon)

The General Problem Solver (GPS) was a theory of human problem solving stated in the form of a simulation program (Ernst & Newell, 1969; Newell & Simon, 1972). This program and the associated theoretical framework had a significant impact on the subsequent direction of cognitive psychology. It also introduced the use of productions as a method for specifying cognitive models.

The theoretical framework was information processing and attempted to explain all behavior as a function of memory operations, control processes and rules. The methodology for testing the theory involved developing a computer simulation and then comparing the results of the simulation with human behavior in a given task. Such comparisons also made use of protocol analysis (Ericsson & Simon, 1984) in which the verbal reports of a person solving a task are used as indicators of cognitive processes.

GPS was intended to provide a core set of processes that could be used to solve a variety of different types of problems. The critical step in solving a problem with GPS is the definition of the problem space in terms of the goal to be achieved and the transformation rules. Using a means-end-analysis approach, GPS would divide the overall goal into subgoals and attempt to solve each of those. Some of the basic solution rules include: (1) transform one object into another, (2) reduce the different between two objects, and (3) apply an operator to an object. One of the key elements need by GPS to solve problems was an operator-difference table that specified what transformations were possible.

## Application

While GPS was intended to be a general problem-solver, it could only be applied to “well-defined” problems such as proving theorems in logic or geometry, word puzzles and chess.  However, GPS was the basis other theoretical work by Newell et al. such as  SOAR  and  GOMS . Newell (1990) provides a summary of how this work evolved.

Here is a trace of GPS solving the logic problem to transform L1= R*(-P => Q) into L2=(Q \/ P)*R (Newell & Simon, 1972, p420):

Goal 1: Transform L1 into LO Goal 2: Reduce difference between L1 and L0 Goal 3: Apply R1 to L1 Goal 4: Transform L1 into condition (R1) Produce L2: (-P => Q) *R Goal 5: Transform L2 into L0 Goal 6: Reduce difference between left(L2) and left(L0) Goal 7: Apply R5 to left(L2) Goal 8: Transform left(L2) into condition(R5) Goal 9: Reduce difference between left(L2) and condition(R5) Rejected: No easier than Goal 6 Goal 10: Apply R6 to left(L2) Goal 11: Transform left(L2) into condition(R5) Produce L3: (P \/ Q) *R Goal 12: Transform L3 into L0 Goal 13: Reduce difference between left(L3) and left(L0) Goal 14: Apply R1 to left(L3) Goal 15: Transform left(L3) into condition(R1) Produce L4: (Q \/ P)*R Goal 16: Transform L4 into L0 Identical, QED

• Problem-solving behavior involves means-ends-analysis, i.e., breaking a problem down into subcomponents (subgoals) and solving each of those.
• Ericsson, K. & Simon, H. (1984). Protocol Analysis. Cambridge, MA: MIT Press.
• Ernst, G. & Newell, A. (1969). GPS: A Case Study in Generality and Problem Solving. New York: Academic Press.
• Newell, A. (1990). Unified Theories of Cognition. Cambridge, MA: Harvard University Press.
• Newell, A. & Simon, H. (1972). Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.

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## Human problem solving

By allen newell and herbert a. simon.

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## Newell and Simon's problem-space theory

Review of the literature, 2.4. information-processing theory and the problem understanding task, 2.4.1. newell and simon's problem-space theory.

Newell and Simon's research into human problem solving, especially their seminal work, "Human problem solving" (1972), still remains a much quoted reference in contemporary information-processing theory and research (Dawson, 1998). Despite the age o f this theory, it was found with a few modifications to be a useful way of structuring thinking

in the area o f interviewer reasoning. The current debate between the classical and the connectionist views of information processing is beyond the scope of this thesis, however readers are referred to Dawson (1998) who provides an excellent coverage o f the issues involved.

Newell and Simon (1972) conducted a wide range of experiments under controlled laboratory conditions into how people (usually undergraduates), approached a range of three-dimensional puzzles, and in particular the Tower o f Hanoi problem. In the Tower o f Hanoi problem participants were presented with three vertical pegs in a row, the first of which had three disks piled on it in order of size; that is the largest disk was at the bottom, the next on top, and so on. The goal o f the problem was to have all the disks piled in the same order on the last peg. However, disks could only be moved in certain ways. Only one disk could be moved at a time, and a larger disk could not be placed on top o f a smaller disk (Eysenck & Keane, 1995, p.363).

Figure 2.2 presents the problem space o f legal moves for the Tower o f Hanoi problem which will be referred to in the discussions below. From Newell and Simon's perspective people went about solving problems by first exploring a range o f possible ways (paths) o f finding a solution. Puzzles, such as the Tower of Hanoi, begin with a point outside the problem space (or maze), and then progress through a series o f moves to the centre - the solution. To achieve the goal o f getting to the centre, the person comes across many junctions where they have to make decisions (e.g., go straight, turn left, and so on). Each of these alternative paths may branch again and again, with some leading to the centre and the solution, and some not. Different strategies can be employed to find one's way inside the problem space (e.g., mark where you have come from, initially take left turns, and so on). These strategies provide the person with a systematic way of searching the problem space, and selecting one path firom a range o f alternative paths to get closer to the solution.

Their findings suggested that the stmcture of a problem could be characterised by a set o f states, beginning with an initial problem state (e.g., standing outside the problem space), involving many intermediate states (e.g., moving through the problem space), and ending with a goal state (e.g., being at the centre of the problem space). People in their studies began with an initial state and "searched" through a space o f alternative mental

States until they reached a goal state. Each of these alternative states can also have alternatives. The number o f these alternatives increases greatly as one moves away from the initial state to the goal state.

In order for people to solve the Tower of Hanoi problem they have to employ a range of cognitive strategies to reduce the number of states which they have to pass through to reach the goal state. Newell and Simon describe such strategies as heuristics. A heuristic strategy is in essence a nonrigorous way of achieving a solution to a problem. While heuristic procedures often lead to solutions, they offer no guarantee o f doing so (Bruner, 1996). Heuristics are contrasted with algorithms, which are methods that produce a definite solution. For example, in the Tower of Hanoi problem, a person could check every state, by starting at the beginning and systematically checking every alternative state until the goal state were achieved. This procedure would take far too long to be efficient, but is guaranteed to solve the problem. Heuristics, on the other hand are "rules of thumb", that may not guarantee a solution to a given problem every time, but most o f the time, thus saving time and effort.

One of the most important heuristic principles proposed by Newell and Simon was means-ends analysis. It consists of three main steps: first, the person notes the difference between the initial state and the goal state, second, they create subgoals to reduce this observed difference, and third, they select an operator that will solve this subgoal. Moves from one state to another are achieved by the application o f "mental operators". As problems may have a large number o f alternative paths, people use strategies to move from the initial state to the goal state efficiently. Thus, people's conception of a problem (i.e. the nature of the initial state), and the knowledge they bring to it (the operators and strategies available to them), make contributions to their problem­ solving behaviour (Newell & Simon, 1972).

Newell and Simon's problem-space theory identifies the various hypothetical states, processes and strategies that people may use to go about solving problems, at least puzzle based problems. The theory also predicts the types o f constraints that will make solving problems difficult, for example, the constraint o f human working memory and the interaction between this and the types o f strategies people use to search it. From a theoretical perspective it provides a normative theory o f human problem solving. The

theory allows for the structure of the problem to be specified and the best solution to the problem to be defined. In puzzle-based research from the 1950s to the present day, it is possible to elaborate the problem space and identify the correct or best solution to the problem by tracing the shortest sequence of moves from the initial state to the goal state. It provides a normative model o f what an "expert" problem solver would do, and how and why people's behaviour diverges from that o f the "expert".

2.4.2. Sum m ary of Newell and Simon's problem-space theory

Newell and Simon's (1972) information-processing theory o f problem solving suggests that when people move from an initial problem state towards a solution state they form a mental representation of the problem, which in this thesis is called a problem map. Research on expert problem solvers (outlined in section 2.7 o f this chapter) shows that they acquire through experience mechanisms for internally representing the problem space. This internal model acts as a precondition for planning, reasoning, anticipating and controlling subsequent cognitive behaviour (Ericsson & Lehmann, 1996).

The problem map undergoes a series of transformations as the problem solver tries to move from the initial problem state to a solution state. These transitions are achieved by the problem solver employing a series of cognitive operations, or strategies, such as means-ends analysis (this is the strategy whereby the problem solver evaluates the difference between the initial problem and the solution state). In summary, Newell and Simon's theory suggests that:

1. Problems have a large number o f alternative paths from the initial problem state to the solution state.

2. The total number o f such states, as generated by mental operators, is called the 'basic problem' space.

3. People's problem-solving behaviour is seen as the production of knowledge states by using mental operators to move from the initial knowledge state to a goal knowledge state.

4. People use their knowledge and various heuristic methods (i.e. means-ends analysis) to search through the problem space to find an efficient path from the initial state to the goal state.

5. All o f these processes occur within the limitations o f the individual's cognitive system, that is their working memory and information processing limitations (i.e. sorting and retrieving information from long-term memory).

6. The contents of people's short-term memory are open to conscious reporting by the individual. This assumption guided much of their work in which they used think-aloud protocols. This is a method whereby individuals say out loud what is going through their minds as they solve problems. The researcher records responses which are analysed later (Eysenck & Keane, 1995, p.363).

• Context-constraints
• Newell and Simon's problem-space theory (You are here )
• THE HYPOTHESIS-TESTING FRAMEWORK TO GUIDE PROBLEM UNDERSTANDING
• THE CHARACTERISTICS OF EXPERT AND NOVICE PROBLEM SOLVERS
• ARGYRIS AND SCHON'S THEORY OF INTERPERSONAL EFFECTIVENESS
• ROBINSON AND HALLIDAY’S RESEARCH ON ACCESSIBLE REASONING
• Critique of model
• Section One (Interviewing)
• Interviewing
• LIMITATIONS OF STUDY ONE
• CONCLUSIONS
• RATIONALE FOR STUDY TWO
• General design and interviewing tasks
• Use o f accessible reasoning statements
• RATIONALE FOR STUDY TWO (A)
• Research questions and hypotheses for study two (a)

Related documents

• Published: 10 February 2018

## Information Processing and Moral Problem Solving

• Cassey Lee   ORCID: orcid.org/0000-0002-4591-6210 1

Computational Economics volume  57 ,  pages 911–922 ( 2021 ) Cite this article

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Herbert Simon and Allen Newell made important contributions to the study of human problem solving within an information processing system (IPS) framework. Contemporary debates and discussions on moral judgment and representation makes little or no reference to their work on problem-solving. This study argues that Simon and Newell’s IPS framework provides a useful integrative framework for the study of moral problem solving. Variations in the boundaries between the task environment and the IPS suggest its potential as a framework for a comparative study of intra and inter-species moral problem-solving.

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Source : Newell and Simon ( 1972 , p. 20)

Source : Newell and Simon ( 1972 , p. 289)

Simon did venture into altruism. See Simon ( 1990 ).

See Shafer-Landau ( 2015 ).

Kymlicka ( 1991 ) draws attention to two different approaches in the social contract tradition, namely, Hobbesian contractarianism and Kantian contractarianism.

Campbell ( 2010 ) has argued that such evaluations have to take into account desert.

There are other ways of organizing theories of justice. Konow ( 2003 ) proposed four theoretical categories of theories of justice based on the following categories, namely: (i) equity and need (ii) utilitarianism and welfare economics (iii) equity and desert and (iv) the dependence of justice evaluation on context.

Philosophers make the distinction between naturalistic and non-naturalistic moralities.

A variety of mathematical and computational approaches to the study of the evolution of ethics have emerged. These include evolutionary game theory and spatial interactions models. One should be careful in analysing these theories. Are the limitations due to the theory per se (e.g. assumption made) or due to something more intrinsic to the evolutionary process.

Interestingly, Newell and Simon have argued that such a program is an observer’s device to describe the system—all that is needed are mechanisms that behave in a way described by the program (ibid, p. 33).

See Newell and Simon ( 1972 , p. 75). Note that for Newell and Simon, the solution could be \(u_{t}\) or \(Q_{t}\) . The iterative process could be entirely internal to the problem solver.

Evolution could shift the boundaries towards the environment—this may partly depend on the intermediaries such as the receptors and effectors. This is also consistent with Buddhism’s emphasis on the body’s sensors. Culture and cooperation could be another way of interpreting the shift in boundaries.

Newell and Simon ( 1972 , p. 100) provides an intriguing visualization of problem solving: “ .., the task of problem solving procedure is to grow a tree of operator sequences that will not branch too luxuriantly, and will include at least one solution path.”

Such a choice may be an internal reflection or one that leads to an action on others (external).

For primers of these field, see, for example, Dukas ( 1998 ) and Stevens ( 2013 ).

Bartels, D. M., Bauman, C. W., Cushman, F. A., Pizarro, D. A., & McGraw, A. P. (2015). Moral judgment and decision making. In G. Keren & G. Wu (Eds.), The Wiley Blackwell hndbook of judgment and decision making . Chichester: Wiley.

Buechner, J. (2008). Gödel, Putnam and functionalism: A new reading of representation and reality . Cambridge, MA: MIT Press.

Campbell, T. (2010). Justice . London: Palgrave Macmillan.

Deigh, J. (2010). An introduction to ethics . Cambridge, MA: Cambridge University Press.

Dukas, R. (Ed.). (1998). Cognitive ecology: The evolutionary ecology of information processing and decision making . Chicago: University of Chicago press.

Greene, J., & Haidt, J. (2002). How (and where) does moral judgment work? TRENDS in Cognitive Science , 6 (12), 517–523.

Guglielmo, S. (2015). Moral judgment as information processing: An integrative review. Frontiers in Psychology , 6 , 1–19.

Hardin, R. (1988). Morality within the limits of reason . Chicago: University of Chicago Press.

Hausman, D. H., & McPherson, M. S. (1996). Economic analysis and moral philosophy . Cambridge: Cambridge University Press.

Hursthouse, R., & Pettigrove, G. (2016). Virtue ethics. In E. N. Zalta (Ed.), The stanford encyclopedia of philosophy (Winter 2016 Edition). https://plato.stanford.edu/archives/win2016/entries/ethics-virtue/ .

Konow, J. (2003). Which is the fairest one of all? A positive analysis of justice theories. Journal of Economic Literature , 41 (4), 1188–1239.

Kymlicka, W. (1991). The social contract tradition. In P. Singer (Ed.), A companion to ethics . Oxford: Blackwell.

McCarthy, J. (1956). The inversion of functions defined by turing machines. In C. E. Shannon & J. McCarthy (Eds.), Automata studies, annals of mathematical studies (Vol. 34, pp. 177–181). Princeton: Princeton University Press.

Mikhail, J. (2008). Moral cognition and computation theory. In W. Sinnott-Armstrong (Ed.), Moral psychology: The neuroscience of morality (Vol. 3). Cambridge, MA: MIT Press.

Mikhail, J. (2011). Elements of moral cognition . Cambridge: Cambridge University Press.

Newell, A., & Simon, H. (1956). The logic theory machine: A complex information processing system (pp. 1–63). Report No. P-868, Rand Corporation.

Newell, A., & Simon, H. (1972). Human problem solving . Englewood Cliffs, NJ: Prentice Hall.

Sen, A. (1987). On ethics & economics . Oxford: Blackwell.

Shafer-Landau, R. (2015). The fundamentals of ethics (3rd ed.). New York: Oxford University Press.

Stevens, M. (2013). Sensory ecology, behaviour & evolution . Oxford: Oxford University Press.

Simon, H. (1978). Information–processing theory of human problem solving. In W. K. Estes (Ed.), Handbook of learning and cognitive processes (Vol. V). Hillsdale NJ: Lawrence Erlbaum Associates.

Simon, H. (1990). A mechanism for social selection and successful altruism. Science , 250 (4988), 1665–1668.

Simon, H., & Schaeffer, J. (1992). The game of chess. In R. J. Aumann & S. Hart (Eds.), Handbook of game theory (Vol. 1). Amsterdam: North Holland.

Sunstein, C. (2004). Moral heuristics and moral framing. Minnesota Law Review , 88 , 156–1597.

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Lee, C. Information Processing and Moral Problem Solving. Comput Econ 57 , 911–922 (2021). https://doi.org/10.1007/s10614-018-9801-1

Accepted : 02 February 2018

Published : 10 February 2018

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DOI : https://doi.org/10.1007/s10614-018-9801-1

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## Human Problem Solving Paperback – February 14, 2023

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First published in 1972, this monumental work develops and defends the authors' information processing theory of human reasoning. Human reasoners, they argue, can be modeled as symbolic "information processing systems" (IPSs), abstracted entirely from physiological bases. Modeling subjects with IPSs yields predictive theories of their problem-solving behavior and performance, and psychological insight into their heuristics and methods.Newell and Simon's previous epoch-making collaborations included the General Problem Solver, the Logic Theorist, and the Information Processing Language. This book is a careful application of those ideas from artificial intelligence - the ideas of AI's first golden age - to cognitive psychology. The authors first develop the formal theory of information processing systems. They then report studies of three symbolic reasoning tasks, and analyze that data using the information processing paradigm. In the final section, they state their comprehensive theory of human problem-solving. The success of the models of cognition given in Human Problem Solving was a major piece of evidence for the physical symbol system hypothesis, which Newell and Simon would first state a few years later. Newell went on to co-develop the Soar cognitive architecture, and Simon to receive the Nobel Prize in Economics. The two jointly received the Turing Award in 1975 for the research program of which Human Problem Solving was the culmination.

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5. The General Problem Solver

6. Theory of problem framing. (Adapted from Newell and Simon 1972

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1. General Problem Solver (A. Newell & H. Simon)

The General Problem Solver (GPS) was a theory of human problem solving stated in the form of a simulation program (Ernst & Newell, 1969; Newell & Simon, 1972). This program and the associated theoretical framework had a significant impact on the subsequent direction of cognitive psychology.

2. Human Problem Solving: Newell, Allen, Simon, Herbert A.: 9781635617924

Human Problem Solving. Hardcover - February 5, 2019. by Allen Newell (Author), Herbert A. Simon (Author) 4.7 12 ratings. See all formats and editions. First published in 1972, this monumental work develops and defends the authors' information processing theory of human reasoning. Human reasoners, they argue, can be modeled as symbolic ...

3. Human problem solving.

Citation Newell, A., & Simon, H. A. (1972). Human problem solving. Prentice-Hall. Abstract Elaborates a comprehensive theory of human problem solving.

4. General Problem Solver

General Problem Solver ( GPS) is a computer program created in 1957 by Herbert A. Simon, J. C. Shaw, and Allen Newell ( RAND Corporation) intended to work as a universal problem solver machine. In contrast to the former Logic Theorist project, the GPS works with means-ends analysis. [1] Overview

5. (PDF) The Problems with Problem Solving: Reflections on the Rise

Newell and Simon's main enduring contribution is the theory that people solve problems via heuristic search through a problem space. This theory remains the centerpiece of our understanding...

6. (PDF) Newell and Simon's Logic Theorist: Historical Background and

Fifty years ago, Newell and Simon (1956) invented a "thinking machine" called the Logic Theorist. The Logic Theorist was a computer program that could prove theorems in symbolic logic from...

7. Human problem solving : Newell, Allen : Free Download, Borrow, and

Human problem solving by Newell, Allen. Publication date 1972 Topics Human information processing, Problem solving Publisher Englewood Cliffs, N.J.: Prentice-Hall ... Simon, Herbert Alexander, 1916-Boxid IA1623006 Camera Sony Alpha-A6300 (Control) Collection_set trent External-identifier

8. Human Problem Solving

Human Problem Solving Allen Newell, Herbert A. Simon Echo Point Books and Media, Feb 5, 2019 - 938 pages First published in 1972, this monumental work develops and defends the authors'...

9. Problem solving and learning.

A. Newell and H. A. Simon (1972) provided a framework for understanding problem solving that can provide the needed bridge between learning and performance. Their analysis of means-ends problem solving can be viewed as a general characterization of the structure of human cognition. However, this framework needs to be elaborated with a strength concept to account for variability in problem ...

10. The problems with problem solving: Reflections on the rise, current

The research paradigm invented by Allen Newell and Herbert A. Simon in the late 1950s dominated the study of problem solving for more than three decades. But in the early 1990s, problem solving ceased to drive research on complex cognition. As part of this decline, Newell and Simon's most innovative research practices - especially their method for inducing subjects' strategies from ...

11. Human problem solving: The state of the theory in 1970.

Elements of a theory of human problem solving. A. Newell J. Shaw H. Simon. Education. 1958. In this paper we shall set forth the elements of a theory of human problem solving, together with some evidence for its validity drawn from the currently accepted facts about the nature of problem….

12. Logic Theorist

Logic Theorist is a computer program written in 1956 by Allen Newell, Herbert A. Simon, and Cliff Shaw. [1] It was the first program deliberately engineered to perform automated reasoning, and has been described as "the first artificial intelligence program".

13. Human Problem Solving by Allen Newell, Herbert A. Simon, Paperback

Newell went on to co-develop the Soar cognitive architecture, and Simon to receive the Nobel Prize in Economics. The two jointly received the Turing Award in 1975 for the research program of which Human Problem Solving was the culmination. This book is also available from Echo Point Books as a hardcover (ISBN 1635617928).

14. Human problem solving by Allen Newell

Edited by ImportBot. import existing book. April 1, 2008. Created by an anonymous user. Imported from Scriblio MARC record . Human problem solving by Allen Newell, Herbert A. Simon, 1972, Prentice-Hall edition, in English.

15. Newell & Simon: The Theory of Human Problem Solving

A. Newell & H. Simon, The Theory of Human Problem Solving; reprinted in Collins & Smith (eds.), Readings in Cognitive Science, section 1.3. Author of the summary: Patrawadee Prasangsit, 1999, [email protected] Cite this paper for: For the purpose of problem solving, humans are representable as information processing systems (IPS)

16. Heuristic Problem Solving: The Next Advance in Operations Research

January - February 1958 HEURISTIC PROBLEM SOLVING: THE NEXT ADVANCE IN OPERATIONS RESEARCH* Herbert A. Simon and Allen Newell Carnegie Institute of Technology, Pittsburgh, Pennsylvania, anid The Rand Corporation, Santa Monica, California

17. Newell and Simon's problem-space theory

Sum m ary of Newell and Simon's problem-space theory. Newell and Simon's (1972) information-processing theory o f problem solving suggests that when people move from an initial problem state towards a solution state they form a mental representation of the problem, which in this thesis is called a problem map. Research on expert problem solvers ...

18. Problem Solving

In the Newell and Simon (1972) approach, the problem solver's internal representation of a problem is referred to as the problem space. This internal representation is distinguished from the problem solving task itself, as defined objectively or from the point of view of an omniscient observer, which is referred to as the task environment.

19. The Role of Problem-Solving in Intelligence: A Newell and Simon

Newell and Simon, influential cognitive scientists, posited that problem-solving lies at the heart of intelligence. This essay delves into the Newell and Simon perspective, explores the significance of problem-solving in intelligence, and offers insights into why this perspective is widely accepted within the field of cognitive science.

20. Information Processing and Moral Problem Solving

Herbert Simon and Allen Newell made important contributions to the study of human problem solving within an information processing system (IPS) framework. Contemporary debates and discussions on moral judgment and representation makes little or no reference to their work on problem-solving.

21. Human Problem Solving

Human Problem Solving (1972) is a book by Allen Newell and Herbert A. Simon. See also. problem solving; References This page was last edited on 21 March 2021, at 23:56 (UTC). Text is available under the Creative Commons Attribution-ShareAlike License 4.0; additional terms may apply ...

22. The Problems with Problem Solving: Reflections on the Rise, Current

The research paradigm invented by Allen Newell and Herbert A. Simon in the late 1950s dominated the study of problem solving for more than three decades. But in the early 1990s, problem solving ceased to drive research on complex cognition. As part of this decline, Newell and Simon's most innovative research practices - especially their method

23. Human Problem Solving: Newell, Allen, Simon, Herbert A: 9781648371943

Newell went on to co-develop the Soar cognitive architecture, and Simon to receive the Nobel Prize in Economics. The two jointly received the Turing Award in 1975 for the research program of which Human Problem Solving was the culmination. This book is also available from Echo Point Books as a hardcover (ISBN 1635617928).