Cognition, Decision Making, Language
Khurshid Ahmad,
Chair of Computer Science
Trinity College, Dublin, IRELAND
11-13th November 2013
Being intelligent being?
Knowledge
Intelligence
Cognition
Being intelligent being?
Herbert Simon in conclusion to his Nobel Lecture (1978) said
that:
“Today, we have a large mass of descriptive data, from both
laboratory and field, that show how human problem solving
and decision making actually take place in a wide variety of
situations. A number of theories have been constructed to
account for these data, and while these theories certainly do not
yet constitute a single coherent whole, there is much in common
among them. In one way or another, they incorporate the
notions of bounded rationality: the need to search for decision
alternatives, the replacement of optimization by targets and
satisficing goals, and mechanisms of learning and adaptation.”
Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture
(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)
Being intelligent being?
Herbert Simon in characterising bounded rationality notes that:
“it is now clear that the elaborate organizations
that human beings have constructed in the
modern world to carry out the work of
production and government can only be
understood as machinery for coping with the
limits of man’s abilities to comprehend and
compute in the face of complexity and
uncertainty”
Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture
(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)
Genesis of the term ‘bounded
rationality’ in Simon
Behavioral theories of rational
choice - theories of
negatively sloping demand
curves could result from a wide
range of behaviors satisfying the
assumptions of
Becker indicates that he denotes
as irrational “[A]ny deviation
from utility maximization.”
Thus, what I have called
strong positive case for replacing
the classical theory by a model
of
bounded rationality
bounded rationality
rather than those of utility
maximization.
“bounded rationality”
is “irrationality” in
Becker’s terminology.
bounded rationality
begins to emerge when we
examine situations
involving decision making
under uncertainty and
imperfect competition.
Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture
(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)
Genesis of the term ‘bounded
rationality’ in Simon
as theory
bounded rationality
as a theory
bounded rationality
the general features of
bounded rationality
must incorporate a
theory of search.
had been proposed as
an alternative to
classical omniscient
rationality
- selective search,
satisficing
Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture
(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)
Genesis of the term ‘bounded
rationality’ in Simon
Satisficing, a "handy blended word combining
satisfy with suffice",[1] is a decision-making
strategy that attempts to meet criteria for
adequacy, rather than to identify an optimal
solution. A satisficing strategy may often be
(near) optimal if the costs of the decision-making
process itself, such as the cost of obtaining
complete information, are considered in the
outcome calculus.
http://en.wikipedia.org/wiki/Satisficing
Genesis of the term ‘bounded
rationality’ in Simon
The word satisfice was coined by Herbert Simon
in 1956. He pointed out that human beings lack
the cognitive resources to maximize: we usually
do not know the relevant probabilities of
outcomes, we can rarely evaluate all outcomes
with sufficient precision, and our memories are
weak and unreliable. A more realistic approach
to rationality takes into account these limitations:
This is called bounded rationality.
http://en.wikipedia.org/wiki/Satisficing
Being intelligent being?
The foundational statement that lays the groundwork for much
of the work in behavioural finance, was made by one of the key
workers in computing (artificial intelligence), psychology
(problem solving), and economics (organisational economics) 
Herbert Simon. For Simon, there are four main areas which
have a symbiotic relationship with behavioural finance:
1. Utility Theory and Human Choice
2. Psychology of Problem Solving
3. Organisational Decision Making
4. Theories of the Business Firm
Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture
(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)
Being intelligent being?
For Simon, there are four main areas which have a symbiotic
relationship with behavioural finance:
Key Symbiosis
Exemplars
Utility Theory and Human Choice Framing that results in
Organisational Decision Making
apparently contradiction to
utility maximisation)
The use of heuristics; bounded
rationality
Decision making by collectives
Theories of the Business Firm
Selective Searching, staisficing
Psychology of Problem Solving
Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture
(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)
Being intelligent being? Cleverly
searching a solution in a large space
Starting from a question “F”, I divide the search
space into E and E’ ; then onto D, and onto C
...until I reach the solution  the colored dices.
F
E
D
C
C
A
A
A
B
B
B
B
A
A
A
A
A
Being intelligent being? Cleverly
searching a solution in a large space
One can traverse all the paths, sequentially or in
parallel, but a clever search strategy will be to
have a good guess, based on experience, to
choose a ‘plausible’ path
E
F
D
C
C
A
A
A
B
B
B
B
A
A
A
A
A
Being intelligent being?
with apologies to Plato
Knowledge about, knowledge by description: knowledge
of a person, thing, or perception gained through
information or facts about it rather than by direct
experience.
Language; Images
Symbols; Planning;
Learning, Thinking;
Creativity
An impersonation of intelligence;
an intelligent or rational being;
esp. applied to one that is or may
be incorporeal; a spirit
COGNITION: The action or
faculty of knowing taken in its
widest sense, including
sensation, perception,
conception, etc., as distinguished
from feeling and volition.
Knowledge, Cognition and
Intelligence
•Knowledge is acquired and disseminated by
intelligent and cognate beings. The terms
knowledge, cognition and intelligence are used
interchangeably.
•And there is a good reason for this: Various
cognitive processes help in converting
information and stimuli into knowledge.
Knowledgeable beings then act intelligently
because of their greater awareness.
Knowledge, Cognition and
Intelligence
Information exchange, processing and decision
making; Knowledge is acquired and
disseminated by intelligent and cognate beings.
Knowledge
Language; Images
Symbols; Planning;
Learning, Thinking;
Creativity
Intelligence
Cognition
Knowledge, Cognition and
Intelligence
Human Information Exchange: The role of cognition, perception
and movement
In everyday language cognition is
used to refer to the 'higher'
mental processes. In psychology
cognition would generally be
taken to include a variety of
mental activities.
Knowledge, Cognition and
Intelligence
Human Information Exchange: The role of cognition, perception and
movement
Cognitive faculties include attention, control, categorisation, creativity, decision
making, language, learning, mental imagery, memory, problem solving, reasoning,
representation.
Perceptive capabilities enable humans to hear, see, smell, taste, and touch. These
capabilities help humans to translate a variety of environmental input, for example,
acoustic, chemical, electromagnetic, mechanical, thermal, into a language which
can be understood by the human nervous system.
Motor skills underpin the cognitive faculties and perceptive capabilities through the
complex network of muscles and nerve fibres for receiving inputs from and
providing output to the external environment.
Cognition, perception and movement helps
humans to exchange
Knowledge, Cognition and
Intelligence
Kinds of Knowledge:
Cognitive psychologists have studied experts, in
the physical, medical and engineering sciences,
involved in problem solving, ranging from
diagnosis, mental calculation, design and
planning for example. The psychologists have
also observed skilled performance in taxi
driving, typing for instance. The observations
have led to six major findings (Glaser
1994:140-141):
Cognitive Processes
• Cognition is a broad term which is
used to refer to activities like
thinking, reasoning, conceiving,
solving problems, learning,
communicating through
language and through other
symbol systems.
19
Cognitive Processes
• Cognition, or rather cognitive, is almost
invariably used whenever an agent (ANIMAL,
HUMAN or ROBOT)
is
• seen to be using abstraction;
• seen to be using complex rules;
• seen to be using
mental imagery;
• said to have intended to act on his,her or its own;
• said to have used a symbol system.
20
Cognitive Processes: Some Definitions
INTELLIGENCE := Perception+Cognition+Motor
Control.
Perception : Reception/analysis of sensory stimuli
Motor control: Pertaining to or characterizing that which involves
the systematic use of muscles;
Cognition: Related to activities that involve abstraction, symbolization,
insight, rule use, imagery, belief, internationality, problem-solving,
language-based communication
21
Percepts, Movements and Concepts?
• The sensory organs receive information
about the world about us; this information
is processed by the brain; and the recipient
ignores/reacts to the processed information.
The reception, processing and reaction
involves muscular movement
• The perception of sound can relate to the
cognition of speech or music; the controlled
movement of limbs can relate to the cognition
of dance movement.
22
Cognitive Processes
• COGNITIVE PSYCHOLOGY is a branch of psychology
that emphasises internal, mental processes.
• In cognitive psychology (COG PSY) human
behaviour is discussed not in terms of its overt
properties but at an abstract level:
•
•
•
•
mental events
Mental representations
beliefs
intentions
23
Cognitive Processes: An example
~ Information Processing
• Any intended input, any idea, image, fact,
knowledge, and so on, counts as information in
COG PSY.
• Processing in COG PSY usually means moving
towards some GOAL by going through a series of
STAGES or a SEQUENCE of acts.
24
Cognitive Processes: An example ~
Information Processing
• Information processing involves cognitive
processes that can deal with the
organization, interpretation and responding
to an incoming stimulation;
PROCESSING :=
ORGANISATION+INTERPRETATION+RESPONSE;
INFORMATION:=
INCOMING STIMULATION
25
Behaviour and Cognition
The Nature of Expertise
One view of human expertise is that some people have spent so
much time solving problems in one particular domain that they
‘know all there is to know’ (nearly) and are able to see any
problem as an instance of a class of problems with which they
have been confronted before.
Once the expert has successfully classified or recognised a new
problem as an instance of a previously experienced problem type,
all the expert has to do is apply whatever solution proved
successful in dealing with that type of problem in the past.
Behaviour and Cognition
Cognitive psychologists have studied experts,
in the physical, medical and engineering
sciences, involved in problem solving, ranging
from diagnosis, mental calculation, design and
planning for example. The psychologists have
also observed skilled performance in taxi
driving, typing for instance. The observations
have led to six major findings (Glaser
1994:140-141):
Behaviour and Cognition
Cognitive psychologists have studied experts,
in the physical, medical and engineering
sciences, involved in problem solving, ranging
from diagnosis, mental calculation, design and
planning for example. The psychologists have
also observed skilled performance in taxi
driving, typing for instance. The observations
have led to six major findings (Glaser
1994:140-141):
Behaviour and Cognition:
A Typology of knowledge
Knowledge Type
Elaboration
Structured, As competence is acquired, elements of knowledge become integrated and
Principled Knowledge the experts store (and retrieve) coherent chunks of knowledge
Procedural The experts’ declarative knowledge appears to be bound with conditions of
Knowledge applicability and procedures for use, e.g. condition-action rules.
Skilled Memory Experts and novices have similar memory storage and retrieval capacities,
but experts appear to use long-term memory in a way it resembles shortterm memory.
Automaticity Proficiency apparently requires that some competent skills must become
automatic, so that conscious processing capacity can be devoted reasoning
and decision making.
Effective Problem Experts appear to spend time in initial analysis of a problem: they assess
Representation the problem, build mental models to make inferences and add constraints
to reduce problem space.
Strong Self- Their experience helps the experts to develop a critical set of selfRegulatory Skills regulatory or metacognitive skills. These skills are used by experts to
control their performance.
Knowledge Management:
Key Issues
• OLD VIEW:
Knowledge should ‘flow’ through an
organisation from the knowledge officers
(top executives) to the knowledge engineers
(middle management), and from the
engineers to the knowledge workers
(experts, practitioners)
30
Knowledge Management:
Key Issues
• POST-INDUSTRIAL VIEW:
Knowledge should ‘flow’ through an
organisation amongst the knowledge
officers (top executives), the
knowledge engineers (middle
management), and the knowledge
workers (experts, practitioners)
31
Knowledge &
Change Management
Post Modern
Organisation
(Pre 1950’s)
Post Industrial
Organisation
(Post 1990’s)
Structure
PASSIVE, STATIC
REACTIVE, DYNAMIC
Products
DURABLE, DULL
DISPOSABLE,
STYLISH
STABLE
CHANGING
GEOGRAPHICALLY
WELL DEFINED
FUZZILY DEFINED
IDENTIFIABLE
RIVALS: WAR OF
CHANGING RIVALS:
Consumer
Needs
Markets
Competition
POSITION
WAR OF MOVEMENT
32
Knowledge Spiral &
Innovation
1980’s
Calculator
Fax
VCR
1985’s
Knowledge
Spiral at
SHARP
1970’s
Mask ROM
Liquid Crystal
Display
CMOS
Semi-conductor
Opto-device
1990’s
Electronic Organiser
Home Fax
Word Processor
LCD TV
Components Technology
33
Knowledge Spiral &
Innovation
1980’s
Calculator
Fax
VCR
Knowledg
e Spiral at
SHARP
P
1970’s
R
Mask ROMO
CMOS
D
Liquid Crystal CONCEPTS/DEVICE
Semi-conductor
U
Display
Opto-device
C
1990’s
T
S Electronic Organiser
Home Fax
Word Processor
LCD TV
1985’s
Components Technology
34
Knowledge Spiral &
Innovation
2000
Personal Office Assistant;
High Definition Television;
Multimedia Systems
1980’s
Calculator
Fax
VCR
1995’s
1985’s
??
Mask ROM
Liquid Crystal
Display
1970’s
CMOS
Semi-conductor
opto device
Flash Memory;TFT;
LCD; Solar Power
1990’s
Electronic Organiser
Home Fax
Word Processor
LCD TV
????
Components Technology
35
Knowledge Spiral &
Innovation
Products/Services
Scientific Progress &
Technical Change
Social Attitudes
36
Knowledge Conversion
Two dimensions of knowledge creation in organisation: explicit and tacit
.
knowledge
Explicit
Knowledge of rationality
Knowledge Sequential knowledge
(OBJECTIVE)
(mind);
(there and then);
Digital knowledge
(theory).
Tacit
Knowledge of experience
Knowledge Simultaneous knowledge
(SUBJECTIVE)
(skills);
(here and now);
Analog knowledge
(practice).
37
Knowledge Conversion
Two dimensions of knowledge creation in organisation: explicit and tacit
.
knowledge
Dimension
Type
Explicit
Symbolic
Implicit
Embodied
Implicit/Tacit
Ingrained
Tacit
Culturally
acquired
38
Knowledge Conversion
Nonaka & Takeuchi’s Knowledge Conversion Modes
Process
Socialisation
Tacit  Tacit
Externalisation
Tacit  Explicit
Internalisation
Explicit  Tacit
Combination
Explicit  Explicit
Task
Share experience; Transfer
skills; Explain models
Articulate knowledge; concepts,
hypotheses
Transfer or acquire knowledge:
by ‘doing’; by teaching; project
work
Systematise knowledge; Evaluation;
Testing
39
Behaviour and Cognition:
Knowledge Evolution
Nonaka & Takeuchi’s Knowledge Conversion Modes
Tacit Knowledge
Explicit Knowledge
To
Tacit
Knowledge
Socialisation
Sympathised
Knowledge
Externalisation
Conceptual
Knowledge
Internalization
Operational
Knowledge
Combination
Systemic
Knowledge
From
Explicit
Knowledge
Behaviour and Cognition:
Knowledge Evolution
Nonaka & Takeuchi’s Knowledge Conversion Modes
Dialogue
Socialisation
Externalisation
Linking
Explicit
Knowledge
Field
Building
Internalisation
Combination
Learning by Doing
Behaviour and Cognition:
Knowledge Evolution
Nonaka & Takeuchi’s Knowledge Conversion Modes
Tacit Knowledge
Explicit Knowledge
To
Tacit
Knowledge
Socialisation
Sympathised
Knowledge
Externalisation
Conceptual
Knowledge
Internalisation
Operational
Knowledge
Combination
Systemic
Knowledge
From
Explicit
Knowledge
Behaviour and Cognition:
Knowledge Evolution
Dialogue
Socialization
Externalisation
Linking Explicit
Knowledge
Field
Building
Internalisation
Combination
Learning by doing
Behaviour and Cognition:
The role of knowledge
Wang (2009) looked at the relationship
between the ‘increasingly complex
financial products in the marketplace’
and ‘investors’ financial literacy’. The
author conducted a questionnaire
survey to see ‘how different male and
female investors’ financial knowledge
and risk-taking behavior are’
(ibid:204).(Wang 2009).
Wang, Alex. (2009). Interplay of Investors’ Financial Knowledge and Risk Taking. The Journal of Behavioral Finance. Vol 10,
pp 204-213.
Behaviour and Cognition:
The role of knowledge
Wang used ‘survey data focusing on investing in mutual funds as tested
knowledge domain and measured behavior’ (ibid:208):
524 participants took part, 317 male and 207 female.
37 questions were used to measure participants’ objective knowledge
regarding investing in mutual funds; these questions were based on the
work in consumer research, especially on attention and comprehension of a
consumer (Celsi and Olson 1988), and based on work in marketing research
on the knowledge of a consumer (Moreau, Lehmann and Markman 2001).
• 10 multiple-choice questions were used to reflect participants’ objective
knowledge regarding investing in mutual funds
• 27 true-false questions were used to measure participants’ objective
knowledge about investing in mutual funds
Celsi, R. L. and J. C. Olson. “The Role of Involvement in Attention and Comprehension Processes.” Journal of Consumer Research, 15, (1988), pp. 210–224.
Moreau, C. P., D. R. Lehmann and A. B. Markman. “Entrenched Knowledge Structures and Consumer Response to New Products.” Journal of Marketing
Research, 38, (2001), pp. 14–29.
Behaviour and Cognition:
The role of knowledge
Distribution of scores in an on-line questionnaire on
‘investment in mutual funds’; 37 questions on the survey
(Wang 2009).
Marks
<40%
≥40% & <50%
≥ 50% & <60%
≥ 60% & <70%
≥ 70% & <80%
≥80%
Total
Number of Percentage of
respondents respondents
9
2%
43
8%
139
27%
152
29%
155
30%
26
5%
524
100%
Grade
Fail
III
II.2
II.1
I
Distinction
Behaviour and Cognition:
The role of knowledge
Wang showed that
1. at ‘least for investors, their objective knowledge,
subjective knowledge, and risk taking are highly
correlated.
2. The gender of the respondent is an important factor
that differentiates investors’ levels of objective
knowledge, subjective knowledge, and risk taking.
Wang has argued that ‘it is investors’ subjective knowledge that
mediates their objective knowledge on risk-taking behavior.
Since male investors have higher subjective knowledge and
objective knowledge than female investors, they often takemore
risks because of the mediation effect of subjective knowledge’
(2009:212) .
Wang, Alex. (2009). Interplay of Investors’ Financial Knowledge and Risk Taking. The Journal of Behavioral Finance. Vol 10,
pp 204-213.
Behaviour and Cognition:
The role of knowledge
The management of financial risk depends upon an
organisation’s base of knowledge, access to capital and ICT
resources, and the accumulated experiential knowledge.
An organisation is in itself an agencement: The knowledge,
capital and technological resources, have to be seen in the
context of the manner in which individuals manage and
operate within the organisations, what is the balance of rights
and duties, rewards and punishments: in short what is the
culture of the organisation, the skills of its owners and workers,
and how is it the agencement works.
Behaviour and Cognition:
The role of knowledge
•There is a need to facilitate the communication across all the facets of the
organisation. Knowledge has to be created, shared, validated and
REGULARLY pruned. Seeding, fertilising, nourishing and pruning are
the HALLMARKS of a sustainable eco system.
•A sustainable eco-system has redundancy built into its operational
mechanisms and allows the system to take advantage of opportunities, to
weather dearth in opportunities, and to recover from disasters and
overindulgence.
•Sustainable eco-systems have well integrated components and have
contingencies to deal with failures in the various sub-systems: Each subsystem is familiar with the operation of other proximate sub-systems.
•A sustainable eco-system is an OPEN system
Behaviour and Cognition:
The role of knowledge
Post Modern
Organisation
Post Industrial
Organisation
Structure PASSIVE, STATIC
REACTIVE, DYNAMIC
Products DURABLE, DULL
DISPOSABLE,
STYLISH
Consumer Needs STABLE
Markets GEOGRAPHICALLY
WELL DEFINED
Competition IDENTIFIABLE
RIVALS: WAR OF
POSITION
CHANGING
FUZZILY DEFINED
CHANGING RIVALS:
WAR OF MOVEMENT
Behaviour and Cognition:
Knowledge Evolution
Nonaka & Takeuchi’s Knowledge Conversion Modes
Tacit Knowledge
Explicit Knowledge
To
Tacit
Socialisation
Risk heuristics
Knowledge
Externalisation
Strategic Vision,
Financial Innovation
From
Explicit
Knowledge
Internalisation
Back Office;
Regulatory Instruments
Combination
Financial Models;
Asset Performance;
News Management
Behaviour and Cognition:
The role of knowledge
Three major financial risk management
disasters usually have three ingredients:
1. Dysfunctional Culture (e.g. ENRON)
2. Unmanaged Organisational Knowledge
(e.g. Barings, Kitter-Peabody, Salomon
Brothers)
3. Ineffective Controls (e.g. 2008 credit
crunch)
Marshall, Chris., Prusak, L., & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence
Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.
Behaviour and Cognition:
The role of knowledge
Three major financial risk management
disasters: Metallgesellschaft Refining &
Marketing
Marshall, Chris., Prusak, L., & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence
Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.
Behaviour and Cognition:
The role of knowledge
Three major financial risk management
disasters: Kidder Peabody
Marshall, Chris., Prusak, L., & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence
Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.
Behaviour and Cognition:
The role of knowledge
Three major financial risk management
disasters: Baring Securities
Marshall, Chris., Prusak, L., & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence
Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.
Behaviour and Financial
Markets
Traditional Finance Theory
Criticism
Behavioural Finance
Response
Theoretical behavioural models are
somewhat ad hoc and designed to explain
specific stylised facts
Behavioural models are based on how
people actually behave based on extensive
experimental evidence, and explain
evidence better than traditional ones
Empirical work is plagued by data-mining
(that is, if researchers set out to find
deviations from rational pricing by running
numerous regressions, ultimately they will
be successful).
Much empirical work has confirmed the
evidence out-of-sample, both in terms of
time-periods as well as cross-sectionally
across different countries
Behavioural finance presents no unified
Traditional risk-based theories do not
theory unlike expected utility maximisation appear to be strongly supported by the data.
using rational beliefs.
Avanidhar Subrahmanyam (2007)Behavioural Finance: A Review and Synthesis. European
Financial Management, Vol. 14, No. 1, 2007, 12–29
Neuroscience and Economics
It can be hypothesized that different criteria are applied
to select one or more features of each of the interacting
modalities – sometimes the features can aggregated to
achieve super-addition, such that the whole is greater
than the sum of the individual features, and at other
times some features can be relegated in importance
such the whole is less that sum leading to sub-addition.
Yet, sometimes a simple addition of the modalities
suffices. The well-known cocktail party effect relies on
the super-addition of low-level linguistic information
with the visual information of facial changes that
enables listeners to ‘listen’ in noisy environments. The
collapse of enterprises and markets on rumours, despite
encouraging quantitative information about the
performance their assets, is the sub-addition of
linguistic information with numerical..
Processes in Prospect Theory
Multi-criteria decision making has a long history in
social sciences and recently have been used in
environmental sciences, images classification and
financial forecasting. The different ways in which
features are aggregated depends on context, data
density and uncertatinity and it appears that the
importance of criteria is measured by means of a
capacity. In effect, it has been found out the
criteria can be aggregated by means of the socalled fuzzy integrals – for cardinal evaluations it
is the Choquet integral appears to be the key and
for ordinal evaluations it is the Sugeno integral.