Transcript THE INFORMATION AGE IN WHICH YOU LIVE Changing the …

Lecture 7
DECISION SUPPORT AND ARTIFICIAL
INTELLIGENCE
Brainpower for Your Business
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STUDENT LEARNING OUTCOMES
1. Compare and contrast decision support
systems and geographic information
systems.
2. Define expert systems and describe the
types of problem to which they are
applicable.
3. Define neural networks and fuzzy logic and
the use of these AI tools.
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STUDENT LEARNING OUTCOMES
4. Define genetic algorithms and list the
concepts on which they are based and the
types of problems they solve.
5. Describe the four types of agent-based
technologies.
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VISUALIZING INFORMATION IN
MAP FORM FOR DECISION MAKING
o Geographic information systems (GISs) allow
you to see information spatially, or in map form.
o Researchers and scientists used a GIS to map
the location of all the debris from the shuttle
Columbia
o The city of Chattanooga uses a GIS to map the
location of its 6,000 trees to help develop a
maintenance schedule
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VISUALIZING INFORMATION IN MAP
FORM FOR DECISION MAKING
o The city of Richmond, VA, used a GIS to
optimize its 2,500 bus stop locations in its public
transportation system
o Sometimes, a picture is worth a thousand words
o Recall from Lecture 1, the form of information
often defines its quality
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VISUALIZING INFORMATION IN MAP
FORM FOR DECISION MAKING
1. Do you use Web-based map services to
get directions and find the location of
buildings? If so, why?
2. In what ways could real estate agents take
advantage of the features of a GIS?
3. How could GIS software benefit a bank
wanting to determine the optimal
placements for ATMs?
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INTRODUCTION
o Phases of decision making
1. Intelligence – find or recognize a problem, need,
or opportunity
2. Design – consider possible ways of solving the
problem
3. Choice – weigh the merits of each solution
4. Implementation – carry out the solution
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Four Phases of Decision Making
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Types of Decisions You Face
o Structured decision – processing a certain
information in a specified way so that you will
always get the right answer
o Non-structured decision – one for which
there may be several “right” answers, without
a sure way to get the right answer
o Recurring decision – happens repeatedly
o Nonrecurring (ad hoc) decision – one you
make infrequently
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Types of Decisions You Face
EASIEST
MOST
DIFFICULT
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DECISION SUPPORT SYSTEMS
o Decision support system (DSS) – a highly
flexible and interactive system that is
designed to support decision making when
the problem is not structured
o Decision support systems help you analyze,
but you must know how to solve the problem,
and how to use the results of the analysis
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Alliance between You and a DSS
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Components of a DSS
o Model management component – consists
of both the DSS models and the model
management system
o Data management component – stores and
maintains the information that you want your
DSS to use
o User interface management component –
allows you to communicate with the DSS
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Components of a DSS
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GEOGRAPHIC INFORMATION
SYSTEMS
o Geographic information system (GIS) –
DSS designed specifically to analyze spatial
information
o Spatial information is any information in map
form
o Businesses use GIS software to analyze
information, generate business intelligence,
and make decisions
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Zillow GIS Software for Denver
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ARTIFICIAL INTELLIGENCE
o DSSs and GISs support decision making;
you are still completely in charge
o Artificial intelligence, the science of making
machines imitate human thinking and
behavior, can replace human decision
making in some instances
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–
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Expert systems
Neural networks (and fuzzy logic)
Genetic algorithms
Intelligent agents (or agent-based technologies)
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EXPERT SYSTEMS
o Expert (knowledge-based) system – an
artificial intelligence system that applies
reasoning capabilities to reach a conclusion
o Used for
– Diagnostic problems (what’s wrong?)
– Prescriptive problems (what to do?)
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Traffic Light Expert System
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What Expert Systems
Can and Can’t Do
o An expert system can
– Reduce errors
– Improve customer service
– Reduce cost
o An expert system can’t
– Use common sense
– Automate all processes
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NEURAL NETWORKS AND
FUZZY LOGIC
o Neural network (artificial neural network
or ANN) – an artificial intelligence system
that is capable of finding and differentiating
patterns
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Neural Networks Can…
o Learn and adjust to new circumstances on
their own
o Take part in massive parallel processing
o Function without complete information
o Cope with huge volumes of information
o Analyze nonlinear relationships
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Fuzzy Logic
o Fuzzy logic – a mathematical method of
handling imprecise or subjective information
o Used to make ambiguous information such
as “short” usable in computer systems
o Applications
– Google’s search engine
– Washing machines
– Antilock breaks
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GENETIC ALGORITHMS
o Genetic algorithm – an artificial intelligence
system that mimics the evolutionary, survivalof-the-fittest process to generate increasingly
better solutions to a problem
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Evolutionary Principles of
Genetic Algorithms
1. Selection – or survival of the fittest or giving
preference to better outcomes
2. Crossover – combining portions of good
outcomes to create even better outcomes
3. Mutation – randomly trying combinations
and evaluating the success of each
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Genetic Algorithms Can…
o Take thousands or even millions of possible
solutions and combine and recombine them
until it finds the optimal solution
o Work in environments where no model of
how to find the right solution exists
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INTELLIGENT AGENTS
o Intelligent agent – software that assists you,
or acts on your behalf, in performing
repetitive computer-related tasks
o Types
–
–
–
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Information agents
Monitoring-and-surveillance or predictive agents
Data-mining agents
User or personal agents
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Information Agents
o Information Agents – intelligent agents that
search for information of some kind and bring
it back
o Ex: Buyer agent or shopping bot – an
intelligent agent on a Web site that helps you,
the customer, find products and services you
want
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Monitoring-and-Surveillance
Agents
 Monitoring-and-surveillance (predictive)
agents – intelligent agents that constantly
observe and report on some entity of interest,
a network, or manufacturing equipment, for
example
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Data-Mining Agents
 Data-mining agent – operates in a data
warehouse discovering information
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User Agents
o User or personal agent – intelligent agent
that takes action on your behalf
o Examples:
–
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–
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Prioritize e-mail
Act as gaming partner
Assemble customized news reports
Fill out forms for you
“Discuss” topics with you
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MULTI-AGENT SYSTEMS AND
AGENT-BASED MODELING
o Biomimicry – learning from ecosystems
and adapting their characteristics to human
and organizational situations
o Used to
1. Learn how people-based systems behave
2. Predict how they will behave under certain
circumstances
3. Improve human systems to make them more
efficient and effective
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Agent-Based Modeling
o Agent-based modeling – a way of
simulating human organizations using
multiple intelligent agents, each of which
follows a set of simple rules and can adapt to
changing conditions
o Multi-agent system – groups of intelligent
agents have the ability to work independently
and to interact with each other
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Business Applications
o Southwest Airlines – cargo routing
o P&G – supply network optimization
o Air Liquide America – reduce production and
distribution costs
o Merck – distributing anti-AIDS drugs in Africa
o Ford – balance production costs & consumer
demands
o Edison Chouest – deploy service and supply
vessels
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Swarm Intelligence
 Swarm (collective) intelligence – the
collective behavior of groups of simple
agents that are capable of devising solutions
to problems as they arise, eventually leading
to coherent global patterns
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Characteristics of Swarm
Intelligence
o Flexibility – adaptable to change
o Robustness – tasks are completed even if
some individuals are removed
o Decentralization – each individual has a
simple job to do
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End of Lecture
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