Loading presentation...

Present Remotely

Send the link below via email or IM

Copy

Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.

DeleteCancel

Make your likes visible on Facebook?

Connect your Facebook account to Prezi and let your likes appear on your timeline.
You can change this under Settings & Account at any time.

No, thanks

Artificial Intelligence and Decision Support Systems

No description
by

Aditya Das

on 21 March 2013

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of Artificial Intelligence and Decision Support Systems

Thank
You ! Brian Rego
Sireesha Yakkali
Aditya Das
Renu Aggarwal
Krutika Reddy Introduction Artificial Intelligence
&
Decision Support Systems Decision making plays a key role in managerial work.
Managers often have to consider large amounts of data, extract and synthesize only relevant information, and make decisions that will benefit the organization.
As the amount of available data grows, so does the need for computer-based aids to assist managers in their decision-making process. Agenda Decision Support Systems
Artificial Intelligence
Expert systems
Neural networks
Genetic algorithms
Intelligent agents Types of Decisions STRUCTURED DECISIONS
Set of steps that if followed in a particular way will always yield the correct answer
Doesn’t involve any feel or intuition
Easily programmed – inputs, processing, outputs

NON-STRUCTURED DECISIONS
One for which there are no rules or criteria that will guarantee a good solution
Usually have several “right” answers
Both controllable and uncontrollable variables Phases of Decision Making Intelligence – find or recognize a problem, need, or opportunity
Design – consider possible ways of solving the problem
Choice – weigh the merits of each solution
Implementation – carry out the solution Decision Support Systems A highly flexible and interactive system that is designed to support decision making when the problem is not structured
Decision support systems help you analyze, but you must know how to solve the problem, and how to use the results of the analysis COMPUTER-AIDED DECISION SUPPORT RECURRING DECISIONS
One that happens repeatedly and, often, periodically (daily, monthly, annually)
Usually based on the same set of rules each time

NON-RECURRING DECISIONS
Ad-hoc or one that you make infrequently
Usually based on different criteria for determining the best solution each time Uses of DSS Decide where to spend advertising dollars
Forecast market and sales trends
Analyze consumer behavior
Analyze drug interactions
Develop airline schedules
Price products Components of DSS Data Management - allows you to store and access information i.e., data warehouse or relational database
Model Management - allows you to store and access models i.e., ANOVA or regression analysis
User Interface Management - allows you to easily manipulate, ask questions, and interpret responses of models i.e., Microsoft Excel, SPSS, STORM, in-house Artificial Intelligence Whereas DSS systems augment business brain power, AI imitates human thinking and behavior
Robots are a form of AI: Mechanical devices equipped with simulated human senses and the capability of taking action on its own
Eg.-a robot lawn mower, called the Lawn-Nibbler, cuts your lawn intelligently avoiding obstacles Uses of Artificial Intelligence By financial analysts:
For managing assets and investing in stocks
By hospitals:
For scheduling staff and diagnosing illnesses
By credit card companies:
For detecting credit card fraud
By police and security organizations:
For predicting criminal behavior patterns Expert systems
Neural networks
Genetic algorithms
Intelligent agents Expert Systems Also called “knowledge-based systems” or “performance support systems”
Captures human expertise and then applies reasoning capabilities to problems and offers advice in the form of a conclusion
Useful for:
1. Diagnostic or “what’s wrong” problems
2. Prescriptive or “what should we do” problems Types of AI systems used in business 70% of Top 500 Companies use AI as part of their Decision Support A DSS augments or assist you in making the decision, but you must know how to reason through the problem and proceed
An Expert System only requires that you input the facts and symptoms of the problem – it contains the know-how for solving the problem (based on human expertise) DSS Vs Expert Systems Example of Expert System People in an Expert System Domain Expert
The person who knows how to solve the problem without the aid of IT
Sometimes called SMEs (subject matter experts)
Knowledge Engineer
The person who builds the expert system
Knowledge Worker
The person who uses the expert system to solve a problem IT in an Expert System Knowledge base
Stores the rules of the expert system
Knowledge acquisition
Used to capture and 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 What Expert Systems Can Do Handle massive amounts of information
Reduce errors
Reduce costs
Improve customer service
Provide consistency in decision making
Maintain an organization’s knowledge asset What Expert Systems Can't Do Handle all types of domain expertise
Solve problems other than those for which they are designed
Apply common sense or judgment to a problem Neural Networks A type of AI system capable of learning because it’s patterned after the human brain
In business, they are used in: securities trading, credit-card fraud detection, real estate appraisal, evaluating loan applications, target marketing, etc. Genetic Algorithms An AI system that mimics the survival-of-the-fittest process to generate better solutions
They are used by business executives to help them decide which combination of projects a firm should invest in
Used in the garment industry to help solve the problem of laying out pieces of the garment and cutting fabric to ensure as little waste as possible.
Used to determine the optimal configuration of fiber optic cable in a network that may include as many as 100,000 connection points
Three evolutionary phases : selection, cross-over and mutation Intelligent Agents An artificial intelligence system that can move around your network performing repetitive tasks independently, adapting itself to your preferences
An intelligent agent is like a travel agent in that it performs tasks that you stipulate FOUR TYPES OF INTELLIGENT AGENTS They can Learn and adjust to new circumstances on their own
Take part in massive parallel processing
Function without complete information
Cope with huge volumes of information
Analyze nonlinear relationships Buyer agents or shopping bots
User or personal agents
Monitoring-and-surveillance or predictive agents
Data-mining agents Conclusion IT can help you be an effective decision maker by assisting you in decision-making tasks with:
Decision support systems (DSS)
Group decision support systems (GDSS)
Geographic information systems (GIS) ADVANCED FORMS OF DSS:
GDSS (Group Decision Support Systems)
GIS (Geographic Information Systems) This is signing off ! IT can help you be an effective decision maker by performing tasks for you with AI using:
Expert systems
Neural networks
Genetic algorithms
Intelligent agents
Full transcript