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Simon’s model of decision-making.

By Dinesh Thakur

Herbert Simon made key contributions to enhance our understanding of the decision-making process. In fact, he pioneered the field of decision support systems. According to (Simon 1960) and his later work with (Newell 1972), decision-making is a process with distinct stages. He suggested for the first time the decision-making model of human beings. His model of decision-making has three stages:

• Intelligence which deals with the problem identification and the data collection on the problem. • Design which deals with the generation of alternative solutions to the problem at hand. • Choice which is selecting the ‘best’ solution from amongst the alternative solutions using some criterion. 

The figure given below depicts Simon’s decision-making model clearly.

We’ll be covering the following topics in this tutorial:

Intelligence Phase

This is the first step towards the decision-making process. In this step the decision-maker identifies/detects the problem or opportunity. A problem in the managerial context is detecting anything that is not according to the plan, rule or standard. An example of problem is the detection of sudden very high attrition for the present month by a HR manager among workers. Opportunity seeking on the other hand is the identification of a promising circumstance that might lead to better results. An example of identification of opportunity is-a marketing manager gets to know that two of his competitors will shut down operations (demand being constant) for some reason in the next three months, this means that he will be able to sell more in the market.

Thus, we see that either in the case of a problem or for the purpose of opportunity seeking the decision-making process is initiated and the first stage is the clear understanding of the stimulus that triggers this process. So if a problem/opportunity triggers this process then the first stage deals with the complete understanding of the problem/opportunity. Intelligence phase of decision-making process involves: Problem Searching: For searching the problem, the reality or actual is compared to some standards. Differences are measured & the differences are evaluated to determine whether there is any problem or not. Problem Formulation: When the problem is identified, there is always a risk of solving the wrong problem. In problem formulation, establishing relations with some problem solved earlier or an analogy proves quite useful.

Design Phase

Design is the process of designing solution outlines for the problem. Alternative solutions are designed to solve the same problem. Each alternative solution is evaluated after gathering data about the solution. The evaluation is done on the basic of criteria to identify the positive and negative aspects of each solution. Quantitative tools and models are used to arrive at these solutions. At this stage the solutions are only outlines of actual solutions and are meant for analysis of their suitability alone. A lot of creativity and innovation is required to design solutions.

Choice Phase

It is the stage in which the possible solutions are compared against one another to find out the most suitable solution. The ‘best’ solution may be identified using quantitative tools like decision tree analysis or qualitative tools like the six thinking hats technique, force field analysis, etc.

This is not as easy as it sounds because each solution presents a scenario and the problem itself may have multiple objectives making the choice process a very difficult one. Also uncertainty about the outcomes and scenarios make the choice of a single solution difficult.

You’ll also like:

• Bounded Rationality Model of Decision Making
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Dinesh Thakur is a Freelance Writer who helps different clients from all over the globe. Dinesh has written over 500+ blogs, 30+ eBooks, and 10000+ Posts for all types of clients.

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Home » Learning Theories » General Problem Solver (A. Newell & H. Simon)

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.

Herbert A. Simon and the Science of Decision Making

Herbert A. Simon (1916-2001)

On June 15 , 1916 , American political scientist , economist , sociologist , psychologist , and computer scientist Herbert Alexander Simon was born. Simon was among the founding fathers of several of today’s important scientific domains, including artificial intelligence , information processing, decision-making, problem-solving, organization theory , complex systems , and computer simulation of scientific discovery . With almost a thousand highly cited publications , he was one of the most influential social scientists of the 20th century.

“(If) there were no limits to human rationality administrative theory would be barren. It would consist of the single precept: Always select that alternative, among those available, which will lead to the most complete achievement of your goals”, – Herbert A. Simon, Administrative Behavior, 1947.

Herbert A. Simon – Early Years

Herbert Alexander Simon was born in Milwaukee, Wisconsin to Arthur Simon, an electrical engineer who had come to the United States from Germany. His mother, Edna Marguerite Merkel, was an accomplished pianist. Simon was educated as a child in the public school system in Milwaukee where he developed an interest in science. Through his uncle’s books on economics and psychology, Simon discovered the social sciences. In 1933, Simon entered the University of Chicago, and studied the social sciences and mathematics. Originally, Simon was interested in biology, but chose not to study it because of his “color-blindness and awkwardness in the laboratory”. Simon received both his B.A. (1936) and his Ph.D. (1943) in political science, from the University of Chicago, where he studied under Harold Lasswell , Nicholas Rashevsky , Rudolf Carnap ,[ 7 ]  Henry Schultz , and Charles Edward Merriam .

Academic Career

After enrolling in a course on “Measuring Municipal Governments,” Simon was invited to be a research assistant for Clarence Ridley , with whom he coauthored the book, Measuring Municipal Activities , in 1938. After graduating with his undergraduate degree, Simon obtained a research assistantship in municipal administration which turned into a directorship at the University of California, Berkeley. From 1942 to 1949, Simon was a professor of political science and also served as department chairman at Illinois Institute of Technology. In 1949, he became a professor of administration and psychology at the Carnegie Institute of Technology (now Carnegie Mellon University), later becoming the Richard King Mellon University Professor of Computer Science and Psychology there. He began a more in-depth study of economics in the area of institutionalism there.

Corporate Decision Making

“The criterion of efficiency dictates that choice of alternatives which produces the largest result for the given application of resources.” – H. Simon (1945), as quoted in [17] 

A Pioneer of Artificial Intelligence

“In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.” Simon, H. A. (1971) “Designing Organizations for an Information-Rich World” 

Herbert Simon has made a great number of profound and in depth contributions to both economic analysis and applications. Simon also was a pioneer in the field of artificial intelligence, creating with Allen Newell the Logic Theory Machine (1956) and the General Problem Solver (GPS) (1957) programs. Both programs were developed using the Information Processing Language (IPL) (1956) developed by Newell, Cliff Shaw, and Simon. In 1957, Simon predicted that computer chess would surpass human chess abilities within “ten years” when, in reality, that transition took about forty years.

Simulating Human Problem Solving

In the early 1960s psychologist Ulric Neisser asserted that while machines are capable of replicating ‘cold cognition’ behaviors such as reasoning, planning, perceiving, and deciding, they would never be able to replicate ‘hot cognition’ behaviors such as pain, pleasure, desire, and other emotions. Simon responded to Neisser’s views in 1963 by writing a paper on emotional cognition, which was largely ignored by the artificial intelligence research community, but subsequent work on emotions by Sloman and Picard helped refocus attention on Simon’s paper and eventually, made it highly influential on the topic. With Allen Newell, Simon developed a theory for the simulation of human problem solving behavior using production rules The study of human problem solving required new kinds of human measurements and, with Anders Ericsson , Simon developed the experimental technique of verbal protocol analysis. Simon was interested in the role of knowledge in expertise. He said that to become an expert on a topic required about ten years of experience and he and colleagues estimated that expertise was the result of learning roughly 50,000 chunks of information. A chess expert was said to have learned about 50,000 chunks or chess position patterns. In 1975 Herbert A. Simon was awarded the ACM A.M. Turing Award along with Allen Newell.

Simon’s three stages in Rational Decision Making: Intelligence, Design, Choice (IDC), MrunaltPatel, CC BY 3.0 <https://creativecommons.org/licenses/by/3.0>, via Wikimedia Commons

Organizational Decision Making and Nobel Prize

Simon was interested in how humans learn and, with Edward Feigenbaum , he developed the EPAM (Elementary Perceiver and Memorizer) theory, one of the first theories of learning to be implemented as a computer program. Simon also has been credited for revolutionary changes in microeconomics, where he introduced the concept of organizational decision-making as it is known today. He was the first to discuss this concept in terms of uncertainty, in the sense that it is impossible to have perfect and complete information at any given time to make a decision. It was in this contribution that he was awarded the Nobel Prize in 1978.

New Institutionalist Economics

In January 2001, he underwent surgery at UPMC Presbyterian to remove a cancerous tumor in his abdomen. Although the surgery was successful, Simon later succumbed to the complications that followed on February 9, 2001. 

References and Further Reading:

• [1] Herbert A. Simon , American Social Scientist, at Britannica Online.
• [2] A tribute to Herbert A. Simon , at CMU
• [3] D. Klahr, K. Kotovsky: A Life of the Mind: Remembering Herb Simon , American Psychological Society, 2001.
• [4] Herbert A. Simon , at The New World Encyclopedia
• [5] Herbert A. Simon, “ Literary Criticism: A Cognitive Approach ” from Stanford Humanities Review, 1995, with peer reviews and critique.
• [6] Herbert A. Simon at Wikidata
• [7]  Rudolf Carnap and the Logical Structure of the World , SciHi Blog
• [8]  Herbert A. Simon,  A Theory of Emotional Behavior . Carnegie Mellon University Complex Information Processing (CIP) Working Paper #55, June 1, 1963.
• [9]  Herbert Alexander Simon   at the   Mathematics Genealogy Project
• [10]  Herbert Alexander Simon   at the AI Genealogy Project.
• [11]  “Herbert A. Simon – Biographical” .  nobelprize.org .  
• [12]  Herbert A. Simon,   A Theory of Emotional Behavior . Carnegie Mellon University Complex Information Processing (CIP) Working Paper #55, June 1, 1963.
• [13]  Herbert A. Simon,  “Motivational and Emotional Controls of Cognition” .   Psychological Review , 1967, Vol. 74, No. 1, 29-39.
• [14] Simon, Herbert A.   ‘Organizations and markets’ ,   Journal of Economic Perspectives , vol. 5, no. 2 (1991), pp. 25–44.
• [15] Frantz, R., and Marsh, L. (Eds.) (2016).   Minds, Models and Milieux: Commemorating the Centennial of the Birth of Herbert Simon . Palgrave Macmillan.
• [16]  Herbert Simon : September 9, 1979, Current Research ,  at Carnegie Mellon University,  cmurobotics  @ youtube
• [17] Harry M. Johnson (1966) Sociology: A Systematic Introduction
• [18] Timeline of Nobel Laureates in Economics , via Wikidata

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The Journal of Problem Solving

Home > Libraries > LIBRARIESPUBLISHING > PUPOAJ > JPS > Vol. 5 > Iss. 1 (2012)

The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm

Stellan Ohlsson , University of Illinois at Chicago Follow

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 verbal protocols - were abandoned. In this essay, I summarize Newell and Simon’s theoretical and methodological innovations and explain why their strategy identification method did not become a standard research tool. I argue that the method lacked a systematic way to aggregate data, and that Newell and Simon’s search for general problem solving strategies failed. Paradoxically, the theoretical vision that led them to search elsewhere for general principles led researchers away from studies of complex problem solving. 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 of how people solve unfamiliar problems, but it is seriously incomplete. In the early 1970s, Newell and Simon suggested that the field should focus on the question where problem spaces and search strategies come from. I propose a breakdown of this overarching question into five specific research questions. Principled answers to those questions would expand the theory of heuristic search into a more complete theory of human problem solving.

Recommended Citation

Ohlsson, Stellan (2012) "The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm," The Journal of Problem Solving : Vol. 5 : Iss. 1, Article 7. DOI: 10.7771/1932-6246.1144 Available at: https://docs.lib.purdue.edu/jps/vol5/iss1/7

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The Structure of Ill-Structured (and Well-Structured) Problems Revisited

• Review Article
• Published: 04 November 2015
• Volume 28 , pages 691–716, ( 2016 )

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In his 1973 article The Structure of ill structured problems , Herbert Simon proposed that solving ill-structured problems could be modeled within the same information-processing framework developed for solving well-structured problems. This claim is reexamined within the context of over 40 years of subsequent research and theoretical development. Well-structured (puzzle) problems can be represented by a problem space consisting of well-defined initial and goal states that are connected by legal moves. In contrast, the initial, goal, and intermediate states of ill-structured (design) problems are incompletely specified. This article analyzes the similarities and differences among puzzles, insight puzzles, classroom problems, and design problems within Gick’s ( Educational Psychologist, 21 , 99–120, 1986 ) theoretical framework consisting of representation construction, schema activation, and heuristic search. The analysis supports Simon’s ( Artificial Intelligence, 4 , 181–201, 1973 ) claim that information-processing principles apply to all problems but apply differently as problems become more ill structured.

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Acknowledgment

Work on this manuscript occurred while the author was a visiting scholar at the Center for the Study of Language and Information, Stanford University and at the Department of Psychology, University of California, San Diego. I thank anonymous reviewers for their many helpful suggestions.

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Stephen K. Reed

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Department of Psychology, University of California, San Diego, La Jolla, CA, 92093, USA

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Reed, S.K. The Structure of Ill-Structured (and Well-Structured) Problems Revisited. Educ Psychol Rev 28 , 691–716 (2016). https://doi.org/10.1007/s10648-015-9343-1

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Published : 04 November 2015

Issue Date : December 2016

DOI : https://doi.org/10.1007/s10648-015-9343-1