Decision Support and Artificial Intelligence

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• Chapter 4
• Decision Support and Artificial Intelligence
• Brainpower for Your Business

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Presentation Overview

• Decision Support Systems
• Collaboration Systems
• Geographic Information Systems
• Artificial Intelligence
• Expert Systems
• Neural Networks
• Genetic Algorithms
• Intelligent Agents

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Introduction

• Types of computer-aided decision support.

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How You Make a Decision

• Four phases of decision making

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Decisions, Decisions, DecisionsHow You Make a
Decision

• Intelligence find or recognize a problem, need,
  or opportunity.
• Design consider ways to solve the problem, fill
  the need, or take advantage of an opportunity.

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Decisions, Decisions, DecisionsHow You Make a
Decision

• Choice examine and weigh the merits of each
  solution, estimate the consequences of each, and
  choose the best one.
• Implementation carry out the chosen solution,
  monitor the results, and make adjustments as
  necessary.

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Decisions, Decisions, DecisionsTypes of
Decisions You Face
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Decisions, Decisions, DecisionsTypes of
Decisions You Face

• Structured decision - processes a certain kind of
  information in a specified way so that you will
  always get the right answer.
• Nonstructured decision - one for which there may
  be several right answers, and there is no
  precise way to get a right answer.

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Decisions, Decisions, DecisionsTypes of
Decisions You Face

• Recurring decision - one that happens repeatedly,
  and often periodically.
• Nonrecurring decision - one that you make
  infrequently.

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Decision Support Systems

• Decision support system (DSS) - highly flexible
  and interactive IT system that is designed to
  support decision making when the problem is not
  structured.

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Decision Support Systems Components of a
Decision Support System
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Decision Support Systems Components of a
Decision Support System

• A typical DSS has three components
• Model management
• Data management
• User interface management
• Model management - consists of both the DSS
  models and the DSS model management system.

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Decision Support Systems Components of a
Decision Support System

• Data management - performs the function of
  storing and maintaining the information that you
  want your DSS to use.
• User interface management - allows you to
  communicate with the DSS.

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Collaboration System

• Collaboration system software that is designed
  specifically to improve the performance of teams
  by supporting the sharing and flow of information.

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Collaboration System Enterprise-wide
Collaboration

• Lotus Notes and Microsoft Exchange are types of
  integrated collaboration systems.

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Collaboration System Supply-Chain Collaboration

• Supply chain management means working with your
  suppliers and distributors in all phases of
  planning, production, and distribution.

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Collaboration System Web-Based Collaboration

• Web-based collaboration tools use the power of
  the Internet to enable people to work together
  effectively and efficiently.
• The peer-to-peer file-sharing feature is combined
  with the ability to create and edit documents
  collaboratively, and to send and receive text and
  voice messages.

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Geographic Information Systems

• Geographic information system (GIS) - a decision
  support system designed to work with spatial
  information.
• Spatial information is any information that can
  be shown in map form, such as roads, the
  distribution of bald eagle populations, and the
  layout of electrical lines.

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Geographic Information Systems
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Artificial Intelligence

• Artificial intelligence (AI) - the science of
  making machines imitate human thinking and
  behavior.
• Robot - mechanical device equipped with simulated
  human senses and the capability of taking action
  on its own.

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Artificial Intelligence

• The AI systems that businesses use most can be
  classified into four categories
• Expert systems
• Neural networks
• Genetic algorithms
• Intelligent agents

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Expert Systems

• Expert system, or knowledge-based system -
  artificial intelligence system that applies
  reasoning capabilities to reach a conclusion.

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Components of an Expert System

• Expert systems are good for diagnostic (whats
  wrong?) and prescriptive (what to do?) problems.

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Expert SystemsComponents of an Expert System

• An expert system combines information, people,
  and IT components.
• Information types include
• Domain expertise the reasoning process that
  will solve the problem.
• Why information.
• Problem facts.

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Components of an Expert System
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Expert SystemsComponents of an Expert System

• People
• Domain expert - provides the domain expertise in
  the form of problem-solving strategies.
• Knowledge engineer IT specialist who formulates
  the domain expertise into an expert system.
• Knowledge worker or user - thats you.

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Expert SystemsComponents of an Expert System

• IT Components
• Knowledge base - stores the rules of the expert
  system.
• Knowledge acquisition used to enter the rules.
• Inference engine - takes the problem facts and
  searches the knowledge base for rules that fit.
• User interface used to run the consultation.
• Explanation module where information is stored.

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Expert SystemsWhat Expert Systems Can and Cant
Do

• An expert system can
• Reduce errors
• Improve customer service
• Reduce costs
• An expert system cant
• Use common sense
• Automate all processes

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Neural Networks

• Neural network (often called an artificial neural
  network or ANN) - an artificial intelligence
  system that is capable of finding and
  differentiating patterns.

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Neural Networks Types of Neural Networks

• Self-organizing neural network - finds patterns
  and relationships in vast amounts of data by
  itself.
• Back-propagation neural network - a neural
  network trained by someone.

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Inside a Neural Network
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Genetic Algorithms

• Genetic algorithm - an artificial intelligence
  system that mimics the evolutionary,
  survival-of-the-fittest process to generate
  increasingly better solutions to a problem.

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Genetic Algorithms

• Genetic algorithms use three concepts of
  evolution
• Selection survival of the fittest.
• Crossover combining portions of good outcomes
  in the hope of creating an even better outcome.
• Mutation randomly trying combinations and
  evaluating the success (or failure) of the
  outcome.

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Intelligent Agents

• Intelligent agent - software that assists you, or
  acts on your behalf, in performing repetitive
  computer-related tasks.
• Four types of intelligent agents include
• Buyer agents or shopping bots
• User or personal agents
• Monitoring-and-surveillance or predictive agents
• Data-mining agents

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Intelligent Agents Buyer Agents

• Buyer agent or shopping bot - an intelligent
  agent on a Web site that helps the customer find
  products and services.

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Intelligent Agents Buyer Agents

• Types of filtering include
• Collaborative filtering - a method of placing you
  in an affinity group of people with the same
  characteristics.
• Profile filtering - requires that you choose
  terms or enter keywords.

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Intelligent Agents Buyer Agents

• Types of filtering continued
• Psychographic filtering - anticipates your
  preferences based on the answers you give to a
  questionnaire.
• Adaptive filtering - asks you to rate products or
  situations and also monitors your actions over
  time to find out what you like and dislike.

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Intelligent Agents User Agents

• User agents (sometimes called personal agents) -
  intelligent agents that take action on your
  behalf.

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Intelligent Agents Monitoring-and-Surveillance
Agents

• Monitoring-and-surveillance agents (also called
  predictive agents) - observe and report on
  equipment.

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Intelligent Agents Data-Mining Agents

• Data-mining agent - operates in a data warehouse
  discovering information.

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Intelligent Agents Components of an Intelligent
Agent

• Autonomy - act without your telling them every
  step to take.
• Adaptivity - discovering, learning, and taking
  action independently.
• Sociability - conferring with other agents.