The development of the modern computer has influenced current ways of thinking about cognition through computer simulation of cognitive processes for research purposes and through the creation of information-processing models.

These models portray cognition as a system that receives information, represents it with symbols, and then manipulates the representations in various ways. The senses transmit information from outside stimuli to the brain, which applies perceptual processes to interpret it and then decides how to respond to it. The information may simply be stored in the memory or it may be acted on. Acting on it usually affects a person’s environment in some way, providing more feedback for the system to process.

Information is defined as a pattern that "rides" on matter or energy. In information sciences patterns and structures are the primary focus of study. One entity can cause a change in another with only an infinitesimal transference of energy. The causer or controller does it with a signal rather than a push.

The General Problem Solver (GPS) 

It is 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.

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.

Principles

Problem-solving behavior involves means-ends-analysis, i.e., breaking a problem down into subcomponents (subgoals) and solving each of those.

Information processing systems

Simon and Newell: An analysis follows what happens from the beginning of a task, such as being given a problem to solve, to the end with the problem solved. The basic theory is that much of the sequence of events can be thought of as the movement, storage and transformation of information.

Major components and information flow

· receptors—senses
· processors--transform, interpret, integrate, select--attention, set, automatic and controlled processes
· memories--long term, short term, working, STSS.
· effectors--muscles, glands

Information enters the system via the receptors and then is transformed and operated on by the processors, some intervening outputs are temporarily stored and others are more permanently stored in memory, outputs are generated which lead to behavior and interaction with the environment.

Procedure

1) Identifying the problem space. The first stage of an analysis of a problem is to identify the initial and goal states (Newell & Simon, 1972). These two states define the boundary of the problem space. The larger the "distance" between the two states the larger the problem space.
2) Identifying some of the intermediate states between the initial and goal state. Only for trivial problems can the solver go directly from the initial state to the goal state. There are usually going to be relatively stable describable intermediate states which need to be reached. Both the problem solver and the analyst may need to know of these.
3) Identifying what needs to be done; the "moves," which enable the problem solver to get from one state to another. In order for a problem to be solved there has to be some procedure by which the situation is transformed from one state to another.
4) Identifying the resources, e.g., knowledge, skills, materiel, personnel and time, needed to execute each of the moves. What is needed in order to reach each of the states from the immediately previous state?

David Marr's approach

The classical view of cognitive science distinguishes at least three different levels of analysis, named according to David Marr terminology:
1) Computation. The problem solver must analyze the task that needs to be done rather carefully. This requires an analysis of the specific parts. What are the inputs to the problem? What are the relations between the parts?
2) Algorithm (and representation). The second task for the problem solver is to specify an effective procedure that one can carry out in order to achieve the goal of the task. This requires a specific characterization of the sequence of operations that operate on a given data base; if the sequence is followed, it will lead to a solution of the problem.
3) Implementation. This requires identifying a set of physical objects which can carry out the algorithm automatically.

Strategies

Trial and error, Hill climbing, Means-ends analysis, subgoals, goal stack, forward chaining, structural analysis.

Other contributions in the area of information processing include D.E. Broadbent’s information theory of attention, learning, and memory; Miller, Galanter, and Pribram’s analysis of planning and problem solving; and, Wickelgren’s General Problem Solving Strategies.

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Computer simulations have played a key role in the development and dissemination of knowledge in various areas. Information processing is no different. Computer simulations have enabled a better understanding of how information processing may be happening inside the human brain. The breakthrough work in the area was done by Simon and Newell and is called the General Problem Solver. The theoretical framework was information processing and attempted to explain all behavior as a function of memory operations, control processes and rules. Computer simulations were created and compared with human behaviour to understand cognitive processes.

Sources:
http://www.acsu.buffalo.edu/~segal/Information.htm
http://www.instructionaldesign.org/theories/general-problem-solver.html
Gale encyclopedia of Psychology