Thursday, January 13, 2011

What is Cognitive Psychology


source: bidorbuy.co.za
What is cognitive psychology?
This paper aims to discuss the basics of cognitive science. It looks at what cognitive science is, what the historical background of cognitive science is. We will also look at the interdisciplinary nature of cognitive science and will study the analogy between mind and computer.
Historical background of cognitive psychology
Let’s look at the historical background of cognitive psychology. Cognitive Psychology has its roots in philosophy. The questions that cognitive psychology tends to answer were first posed by philosophers. Let’s look at the contribution of major philosophers.
Plato is considered the founder of all modern science.
The main ideas and contribution of Pluto are:-
1-      Ideas are innate
2-      Visible world is an illusion
3-      The objects we see are the shadows of reality
Introspection is the process of observing the operations of one’s own mind with a view to discovering the laws that govern the mind, etc.

Let’s see an example of introspection:
Suppose you have to explain the way to nearest hospital from your home. Imagine doing that in your mind. You may see some images or words in your mind. What you observe in your mind constitutes introspection.
Introspection is criticised as an unscientific method because the imagination of people may differ. Moreover, people may not be able to report themselves correctly and there is no way to verify what they are saying.


(Experiments of Pavlov)
Ivan Pavlov discovered the classical conditioning and the laws of conditioning.
He did a series of experiments with his dog. He use to ring the bell before giving food to the dog and observed that the saliva level of the dog increased just by ringing of the bell even though no food was there. This is known as classical conditioning.
B.F. Skinner
Skinner held the view that if behaviour is followed by a reward, it will be learned.
Skinner viewed mind as a black box and was interested in the input/output model. Something goes into the system and something comes out of the system.
Information processing approach came out of two main streams:
i)                    Human Factors research
ii)                   Information theory
Noam Chomsky(1928-current):
Noam Chomsky was an American linguist who argued that language is the proof that human behaviour is much more than mere input-output responses.
There are things happening in the head which we cannot reproduce.
Computers
Computers are important and every field of life and in many ways relevant to cognitive science.
Artificial Intelligence
Artificial Intelligence (AI) is the branch of computer science that deals with intelligent behaviour, learning and adaptation in machines. Research in AI is concerned with producing machines to automate tasks requiring intelligent behaviour.
There is an analogy between computers and brain.
We cannot replicate human intelligence.
Many psychologists have worked in perception, memory, cognitions, etc.
Information Processing
Information processing is about how the input is transformed into output.
Human beings were regarded as machines but information processing input.
How can humans transform input to output?
Let’s see an example:
If you see a snake when you are travelling.
 What will you do? Either you will run away or try to kill it.
Seeing the snake is the sensation. Running away is the behaviour.
For psychologist the basic issue is that how a sensation is transformed into behaviour.
The special thing about information processing approach is that it allows us to separate different processes into subsystems.
We can identify different stages of processing.
- levels of processing
- Stages of processing
               
                - Hardware level description
                - Software level description

Hardware level description

Network of neurons (brain cells) can be considered as hardware.
It may be impossible to know how ideas, etc. are generated.
-
- Visual sensation
- Sensory neurons
- Visual cortex
Software level description
Sensation
Sensory storage – low level processing
If we see something that information is stored somewhere for microseconds.
Filter – selective attention
- Short-term memory/ Working memory – RAM of computer

STM starts processing information.
Then we recognize what we have seen.
Where this information does comes from?
It comes from long term memory.
- Long-term memory- like a huge hard disk with infinite capacity.
Long term memory has memory from all experiences.
Working Memory
Working/operational memory draws information from long term memory and it compares sensation with it.


Hardware Example
- you are listening to a lecture
- There are other things happening around you.
- All of these sounds are entering your ear
*- Your auditory nerve carries this information to the brain.
- The brain performs complex analysis on the information
The brain generates a thought such as “I understand  this.”
Software level Example

You are listening to the lecture
-          Other sounds are also getting to your ears
-          All the information is held for a brief period in sensory memory.
-          Most of this information is discarded and only selected information, the lecture is passed on to the working memory for processing/
-          Working memory uses resources in the long term memory for understanding the lecture.
Let’s see an experiment:
Suppose you are tapping a rhythm with your hands like tapping with your left hands 4 times and with right hand one time and counting 500, 497, 494 simultaneously.
-          You can see that both tasks with suffer
-          Some people may be able to do one thing at the expense of other
-          But not both equally well at the same time
We cannot do the same simultaneously because our working memory has some limits.
However, you can drive and smoke at the same time because you are used to the process. Otherwise, you cannot do two things at the same time.
Limited Resource Models
- Some cognitive psychologists have looked at the phenomena as limited resource issues.
(Limited amount of attention is available)
- Others have seen it as a filter issue:
There is no shortage of attention, but the system has filters with narrow bands sort of like bottlenecks.
Analogy with computers
Experimentation
- What distinguishes a cognitive psychologist from a pure theoretician is the process of experimentation.
- We have a hunch
- Experiments are conducted
Experimentation differentiates cognitive scientists from other fields like philosophy, AI, etc.
- We can do two easy things at the same time.
By easy thing is meant that the person performing the task is used to it and it is almost automatic.
However, we may not be able to do two difficult things at the same time.
As:
- There is a limited resource available to us.
There are possibly filters at the stages of processing.

We  may not be able to do two difficult things at the same time.
There is a limited resource available to us.
There are possibly filters in the stages of processing
Filters are needed when there is a limited capacity because everything cannot be processed.
- There are possibly filters between different stages of experiment
- Models are developed using information processing approach
- Experiments can be designed to test hypotheses regarding each stage of processing.

Intelligence:
-          Intelligence is not treated well in the fields of abnormal psychology and clinical psychology.
-          Unintelligent methods are being used in those fields to understand intelligence
Cognitive psychology seeks to understand intelligence in all its richness, in all its beauty, completely and the wealth of information that is available.

Tuesday, January 11, 2011

What is Cognitive Science?

What is Cognitive Science?
Cognitive science is the science of mind and behaviour.
Feature # 1:
Cognitive science study MIND and BEHAVIOR
Mental states are processes inside the brain
-          Emotions, knowledge of language, reasoning
The behaviour caused by these processes
-          Facial expression
Feature # 2:
Cognitive science is a science
-          Theories and hypothesis have to be tested
-          How? Check whether they can explain the data for experimentation and observation
Why study cognitive science?
-          Intellectual value
-          Practical value
o   Education
o   AI and technology
o   Medical Application
-          Educational value
-          Entertainment value
Methodology of Cognitive Science
Some distinct features about research methods and explanations in cognitive science
-          Brain-based explanations
-          Functional explanations
-          Interdisciplinary
-          The computation method
Brain-based explanations
The mind is explained in the terms of physical processed in the brain
How to deal with this complex system?
1)      Functional Approach
Understand the functions of different systems of the brain and see how they interact
-          Visual areas, language, emotions
2)      Inter-disciplinary Approach
Psychology – cognitive psychology, development psychology
Linguist – syntax, semantics, phonology
Neuroscience – brain stem, localization
Computer science – AI, Computer models
Philosophy – theoretical foundation

The computer model of the mind
The mind is like a computer
A distance feature of cognitive science

What is computer model?
The mind is an information processing system
Information processing is best explained by computers and symbols
Information processing in the brain neural computations involving mental representations

The computer model of the mind
The mind is like a computer
A distinctive feature of cognitive science
Mental Representations
Mental representations are symbols in the brain that have meaning or encode information
Thinking P ~ activating a mental representation that means P
Why should we accept the computational model of mind?
Some reasons:
-          Information processing does seem to be  a distinctive feature of mind
-          Mental representations are useful in explaining lots of mental phenomena
-          We can observe mental representations
Information Processing in the Mind
Perception
Acquiring real time information about the surrounding environment
Language Use
Making use of information about syntax, semantics and phonology
Reasoning
Combining different sources of information, deriving new information
Action
Making use of information in action, planning and guidance
Memory
Storing and retrieving information
They help us explain lots of things
Example: Syntactic disambiguation
Two methodologies consequences of computer model
Computer models can be built to test theories of mental processes
There are different levels of analysis for a complex information processing system.
Three levels of description
A complete understanding of a computational system has to invoke three kinds of levels:-
Task: what the system is capable of doing?
Algorithm: which computational procedures are used
Implementation: how the computations are implemented
Example:
Task: Multiplication
Algorithm: Input numbers x and y
Output numbers in row x and column y
Implementation: human beings and paper


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Cognitive science

Cognitive science
Cognitive science is an interdisciplinary study of mind and intelligence emphasizing philosophy, psychology, artificial intelligence, neuroscience, linguistics and anthropology.
Methods
Cognitive science is an interdisciplinary field. Although it was unifying theoretical framework for various fields it encompasses, the methods for research and experimentation is diverse.
Let’s see what various methods various fields of knowledge bring to the field of cognitive science.
Cognitive psychology
The primary means in cognitive psychology is experiments with human subjects. Another method which is used today is theorizing and computation modelling.
Psychologists bring people to the laboratory and examine their thinking under controlled conditions.
Psychologists have experimentally examined the kinds of mistakes people make in deductive reasoning, the ways people form and apply concepts, the speed of people mental images, the performance of people solving problems using analogy.
Psychological experiments need to be interpretable within a theoretical framework that postulated mental representations and procedures. One of the best ways of developing theoretical frameworks is by forming and testing computational models intended to be analogous to mental operations.
To complement psychological experiments on deductive reasoning, concept formation, mental imagery, and analogous problem solving, researchers have to complement psychological experiments on deductive reasoning, concept formation, mental imagery, and analogous problem solving; researchers have developed computational models that simulate aspects of human performance.
Design, building and experiment within computational models is the central method of artificial intelligence.
Neuroscientist
Like cognitive psychologist, neuroscientist often perform controlled experiments, but their observations are very different, since neuroscientist are directly concerned with the nature of the brain.
With animal subjects, researchers insert electrode and record the firing of individual neurons.
Moreover, it has become possible in recent years to use magnetic and positron scanning devices to observe what is happening in different parts of the brain while people are doing various mental processes.
Philosophy
Philosophy is important to cognitive science because it deals with fundamental issues that underlie the experimental and computational approach to mind.
Representation and Computation
The central hypothesis of cognitive science is that thinking can be best understood in terms of representational structures in the mind and computational procedures that operate on those structures.
Most work in cognitive science assumes that the mind has mental representations analogous to computer data structure and computational procedures similar to computational algorithms.
Cognitive science works with a 3-way analogy with the mind, the brain and the computer.
Theoretical Approaches
Formal Logic
Formal logic provides some powerful tools for looking at the nature of representation and computation. Propositional and predicate calculus same to express many complex kinds of knowledge and many inferences can be understood in terms of logical  deduction using inference rules.
The explanation scheme for logical approach
Explanation target:
Why do people make the inferences they do?
Explanatory pattern:
-          People have mental representations similar to sentences in predicate logic                 
-          People have deductive and inductive procedures that operate on those sentences
-          The deductive and inductive procedures, applied to the sentences, produce the inferences
Much of human knowledge is naturally described in terms of rules of the form IF … THEN …, and many kinds of thinking such as planning can be modeled by rule-based systems. The explanation schema used is:
Explanation target:
·         Why do people have a particular kind of intelligent behavior?
Explanatory pattern:
·         People have mental rules.
·         People have procedures for using these rules to search a space of possible solutions, and procedures for generating new rules.
·         Procedures for using and forming rules produce the behavior.
Computational models based on rules have provided detailed simulations of a wide range of psychological experiments, from crypt arithmetic problem solving to skill acquisition to language use. Rule-based systems have also been of practical importance in suggesting how to improve learning and how to develop intelligent machine systems.
Concepts
Concepts which partly correspond to the words in spoken and written language are an important kind of mental representations.
The explanatory schema use concept based system is:
Explanatory target:
-          Why do people have a particular kind of intelligent behaviour?
Explanation pattern:
·         People have a set of concepts, organized via slots that establish kind and part hierarchies and other associations.
·         People have a set of procedures for concept application, including spreading activation, matching, and inheritance.
·         The procedures applied to the concepts produce the behavior.
·         Concepts can be translated into rules, but they bundle information differently than sets of rules, making possible different computational procedures.
Analogies

Analogies play an important role in human thinking, in areas as diverse as problem solving, decision making, explanation, and linguistic communication. Computational models simulate how people retrieve and map source analogs in order to apply them to target situations. The explanation schema for analogies is:
Explanation target:
·         Why do people have a particular kind of intelligent behavior?
Explanatory pattern:
·         People have verbal and visual representations of situations that can be used as cases or analogs.
·         People have processes of retrieval, mapping, and adaptation that operate on those analogs.
·         The analogical processes, applied to the representations of analogs, produce the behavior.
The constraints of similarity, structure, and purpose overcome the difficult problem of how previous experiences can be found and used to help with new problems. Not all thinking is analogical, and using inappropriate analogies can hinder thinking, but analogies can be very effective in applications such as education and design.

Thus in cognitive science we used various kinds of computational models .
References:

http://plato.stanford.edu/entries/cognitive-science/