Week 5 - Introduction to Artificial Intelligence Applications
Assignment:
Find a journal article (or conference proceedings paper)
that describes an expert system/artificial intelligence
application related to your field of research or interest.
You may find such papers in the following journals:
Applied Engineering in Agriculture, Transactions of ASAE,
or Applied AI in Natural Resources.
There are many other possible places to find an article too.
Read the article and prepare a brief review that is emailed
to me (engelb) by the end of week 6.
If possible, indicate what software was used and describe
the benefits of expert system/artificial intelligence approach
in solving the problem.
Review this document.
Read Chapters 2 (The Representation of Knowledge)
and 6 (The Design of Expert Systems)
in the text "Expert Systems: Principles and Programming."
WWW sites of possible interest (these are optional):
WWW Virtual Library: AI
Electronic AI Journals
Important Terms and Concepts:
In this section of the course, we will explore expert systems
(ES) which have grown from the artificial intelligence (AI)
field. ES have many possible applications within agriculture and
engineering. They may be used to complement the other systems
analysis and engineering techniques that we examine.
It is important to understand the human decision making process
to best understand how one should develop ES and decision support
software. Follow this link to learn more about
decision making and decision support.
The following sections highlight materials from your reading and
other sources.
ES definition/properties
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"reasons" by symbol manipulation
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solves problems with a high degree of complexity and difficulty
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expertise is exemplified by high-level rules,
the avoidance of a blind search, and high performance
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uses heuristics or "rules of thumb" to arrive at an answer
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reformulates the problem from lay terminology
into a form suitable for expert rule application
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utilizes a well structured knowledge base sufficient for the
solution of problems within a relatively narrow domain
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provides explanations of its line of reasoning and
answers questions about its knowledge
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integrates new knowledge on an incremental basis without
detrimentally affecting previous knowledge or control strategies
Expert
An expert is a person who, because of training and experience,
is able to do things the rest of us cannot;
experts are not only proficient but also smooth and efficient
in the actions they take.
Experts know a great many things and have tricks and caveats for
applying what they know to problems and tasks; they are also
good at plowing through irrelevant information
in order to get at basic issues, and they are good at
recognizing problems they face as instances of types
with which they are familiar.
Underlying the behavior of experts is the body of operative
knowledge we have termed expertise.
It is reasonable to suppose,
therefore, that experts are the ones to ask when we
wish to represent the expertise that makes
their behavior possible.
Comparing Humans and ES
Good News
human expertise ES
perishable permanent
difficult to transfer easy to transfer
difficult to document easy to document
unpredictable consistent
expensive affordable
Bad News
human expertise ES
creative uninspired
adaptive needs to be told
sensory experience symbolic input
broad focus narrow focus
common sense knowledge technical knowledge
Categories of ES Applications
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Interpretation - inferring situation description from sensor data
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Prediction - inferring likely consequences of given situations
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Diagnosis - inferring system malfunctions from observables
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Design - configuring objects under constraints
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Planning - designing actions
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Monitoring - comparing observations to expected outcomes
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Debugging - prescribing remedies for malfunctions
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Repair - executing plans to administer prescribed remedies
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Instruction - diagnosing, debugging, and repairing student
behavior
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Control - governing overall system behavior
Agricultural ES Applications
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marketing
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diagnostics
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pests
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machinery
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livestock
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animal health
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garden and lawn disease
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cropping problems
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environmental control
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crop processing/storage
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engine problems
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equipment problems
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hydraulic malfunctions
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planning
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strategic
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tactical
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government program advisor
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pest management
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weather-related advisories
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financial strategies
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crop mixes
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waste strategies
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equipment purchases
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enterprise mix, expansion
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soil/site evaluation for construction
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facilities selection and design
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government program interpretation
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operations management
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short-term finances
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animal production
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crop production
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marketing
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planting/harvest decisions
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resource conservation
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spraying scheduling
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fertilizer applications
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expert control
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university/government
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information transfer
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grantsmanship
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interpret simulations
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monitor/control equipment
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troubleshoot equipment problems
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set research funding priorities
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statistical design of experiments
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improve design of educational units
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executive CAI modules
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interfacing with interactive video
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reduce delays/costs of consultants
Requirements for ES development
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task does not require common sense
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task requires only cognitive skills
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experts can articulate their methods
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genuine experts exist
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experts agree on solution
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task is not too difficult
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task is not poorly understood
When is ES Development Justified
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task solution has a high payoff
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human expertise being lost
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human expertise scarce
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expertise needed in many locations
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expertise needed in hostile environments
Characteristics that make use of ES appropriate
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task requires symbol manipulation
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task requires heuristic solutions
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task is not too easy
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task has practical value
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task is of manageable size
Potential Limitations in ES Development
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lack of resources
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hardware
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knowledge engineer
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software
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expert(s)
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ES not good at:
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representing temporal knowledge
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representing spatial knowledge
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performing common sense reasoning
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recognizing the limits of their ability
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handling inconsistent knowledge