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/
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