Approaches to Problem Solving in Cognitive Psychology

There are various kinds of problems in our everyday life. We face problems each and every day. We use problem-solving when we want to reach a goal, and that goal easily not available. It involves those situations in which something is blocking our successful  completion of our target or goal/task. 

There are various approaches to Problem Solving on which we will have a brief look. We will discuss the traditional approach to modern approaches.

1)Traditional Approaches:- These approaches explain problem-solving on the principles of associative learning which has been taken from the studies of Classical and Instrumental Conditioning.

2)Gestalt Approaches:- Gestalt psychologists emphasized the importance of the structure of the problematic situation and the formation of new ideas with the combination of old ideas. Gestalt psychologists were focused on that how people solve problems if objects are rearranged.

3)Information Processing and Computer Simulation:- There are number of researchers who has tried to program the computer to perform the tasks and work that humans do. These computer simulation researchers has had great influence on the psychology of human cognitive processes. This method consists to program a computer to work in specific manner.

3.1) The General Problem Solver:- This program was equipped with the equivalent of:

A limited capacity working memory characterized by rapid storage and retrieval

A large capacity long term memory characterized by relatively low storage and

retrieval

A serial processor that performs one operation at a time

A reliance upon heuristics, rather than algorithms that would require a large

number of high speed calculations.

Newell and his colleagues collected verbal protocols that were used and kept as

a record of individuals talking aloud as they solved problems. Then they transcribed

these lengthy records carefully to see if they could find general heuristics that

emerged. It introduced a way of conceptualizing problem that is adopted in most

contemporary theories of problem solving.

The General solver (GPS) assumes that the matter solver represents

a problem as a problem space which consists of a set of nodes, each node

corresponding to a state of data about the matter . The problem solver

begins at the initial state of information and seeks to convert it into the goal state

by applying operators, which are actions that are permitted so as to maneuver 

from one state of another. Problem solving, then, requires a constructive search

during which the solver builds up a drag space, which leads from the initial

to goal state employing a set of allowed operators.

3.2) Means End Analysis

This was recognized as a general problem solving heuristic which involves a

search for operations that will reduce the difference between present state of

knowledge and the goal state.

3.3) Wickelgren’s General Problem Solving Strategies

Wickelgren’s view of problem solving is predicated on information science theories

such as GPS. consistent with this view, a proper problem contains three sorts of 

information:

A statement of the initial state.

Description of the goal state.

Description of set of operation or transformations.

A solution are often defined as a sequence of state or actions which helps to represent

in a diagram called the State Action Tree. The nodes or branch points on the tree

represent all the possibly different problem states that would result from all the

different action sequences.

 

Wickelgren argues that there are seven general problem solving techniques for searching the state

action tree.

i) Inference: Deducing from the explicitly stated goals givens, and operations

stated within the problem

ii) Classification of action sequences: organising possible sequences of actions

(or operations) that are equivalent as far because the problem cares . These

are called equivalence classes.

iii) State evaluation and hill climbing: state evaluation involves defining a

quantitative evaluation function which will be calculated for all possible

problem states and hill climbing involves choosing the action to be taken

next which will have an evaluation that's closest to the goal.

iv) Subgoals: This stage involves checking out sub goals involve breaking down

the problem into sub goals to form it simpler.

v) Contradiction: deriving some inference from the givens that's inconsistent

with the goal state to narrow down the state action tree during a systematic

fashion by eliminating possibilities that would possibly not work.

vi) Working backward: It involves beginning with the goal state and dealing 

backward from it.

vii) Finding relations between problems: finding relations between the new

problems and problems solved previously.

4)NEWELL’S APPROACH

It is very natural to consider problems as being solved through the exploration of

different paths to an answer . Taker maze for instance . In this, you begin from a

point outside the maze then progress through it to the center. On your way,

you reach junctions where you've got to settle on between going straight on, turning

to the left or right, or turning back. Each of those alternative paths may branch

again and again in order that , within the maze as an entire , there are many alternative

paths (only a number of which can cause the center). Different strategies are often 

used to find one’s way through a labyrinth.

The strategies provide you with a scientific method for searching the maze and

help you to pick one from among the various alternative paths.

Newell and Simon used parallels to those basic ideas to characterize human

problem solving behavior.

They suggested that the target structure of a drag are often characterized as:

i) a group of states, beginning from an initial state (e.g. standing outside the maze),

ii) involving many intermediate states (e.g. moving through the maze), and

iii) ending with a goal state (e.g. being at the center of the maze)

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