Generic Tasks
by
Ihab M. Amer
Graduate Student
Computer Science Dept.
AUC, Cairo, Egypt
Agenda
• Introduction
• Generic Tasks
› Definition
› Main Concept
› Some GTs and their Specs
› Generic Task Tools
› GTs as Building Blocks
• Conclusion
Introduction
• Weakness of the (Rule, Frame, and Logic)
Level
› It assumed that there is something called
domain knowledge that needs to be
acquired quite independent of the
problems one might wish to solve, , so it
did not distinguish between different types
of knowledge-based reasoning.
› This contradicts the interaction problem.
The Interaction Problem
• It States that
“representing
knowledge for the
purpose of solving some problem is
strongly affected by the nature of the
problem and by the inference strategy
to be applied to the knowledge.”
Introduction (cont’d)
The shortage in these systems encouraged
scientists to present a higher level
methodology in KBS named as Generic Tasks
(GT). The relationship of the constructs at the
generic task level to the rule-frame-logic level
is analogous to that between high-level
programming languages and assembly
languages in computer science.
Generic Tasks
• Definition
› Generic tasks are simply, basic combinations of
knowledge structures and inference strategies
that are powerful for dealing with certain kinds
of problems.
Main Concept
• The appearance of generic
tasks is considered to be a
good step in satisfying the
interaction problem, since
each problem type has a
distinct strategy type that
uses a distinct knowledge
type to solve it.
• Notice here why we used
the term “Type”.
Main Concept
• The appearance of generic
tasks is considered to be a
good step in satisfying the
interaction problem, since
each problem type has a
distinct strategy type that
uses a distinct knowledge
type to solve it.
• Notice here why we used
the term “Type”.
• This may be clear in the
opposite figure:
Some GTs and there Specs
There are several types of generic tasks.
They are developed for problems that may
frequently appear and need solution. Here,
we briefly describe some of them in order
to recognize the importance of the GT
concept.
Hierarchical Classification
• Input: Given a situation description in terms of features.
• Output: Classify it as specifically as possible, in a
classification hierarchy, determining what categories or
hypotheses apply to the situation.
• Inference & Control: The establish-refine strategy
specifies that when a hypotheses is confirmed or likely (the
establish part), its subhypotheses (children of the node) should
be considered (the refine part).
•
If a hypotheses is rejected, its subhypotheses are also ruled-out.
Example Use: Medical diagnosis can be often viewed
partly as a classification problem.
GT Hypothesis Matching
• Input: Given a concept (a hypothesis) and a set of data
•
•
(features) that describe the problem state.
Output: Decide how well the concept matches the situation.
The task is a form of recognition.
Inference & Control: At each level, a degree of confidence
in the presence of a feature is computed from the features that
constitute evidence for it, and this is performed recursively until
a degree of confidence for the concept is computed. The basic
theory is that recognition of a complex concept is performed by
hierarchically computing intermediate abstractions from raw data.
• Example Use: Recognition can be performed by
means of this strategy. e.g. the concept may be a disease
and the data may be the patient data relevant to the disease,
and we wish to know what the likelihood of the disease is.
GT Abductive Hypothesis
Assembly
• Input: Given a situation description and a set of hypotheses
each explaining some aspects of the situation and each with
•
some plausibility value.
Output: Construct a composite hypothesis that is the best
explanation of the situation.
• Inference & Control: Assembly and criticism alternate.
At each stage during assembly the problem solving is driven by
an attempt to explain the most significant datum remaining
unexplained.
• Example Use: This Task is a diagnostic subtask in
diagnostic reasoning as well as in theory formation in
science.
Generic Task Tools
• Of course researchers needed tools to watch the effect of
using GTs in problem solving. This has pushed them to
release some versions for different GT tools. Here we are
going to mention some of them.
• CSRL (Conceptual Structures Representation Language)
(Bylander & Mittal in 1986) for hierarchical classification.
• HYPER (HYPothethes matchER)
(Johnson in 1986) for hypotheses matching.
• PEIRCE (named after C. B. Peirce, who first described the
form of inference known as abduction.
(Punch, Tanner and Josephson in 1986 ) for GT
Abductive Hypothesis Assembly.
GTs as Building Blocks
• Integration between different types of GTs happens in
order to solve complex problems.
• If a certain GT needs information which can be available
by another one, then it may call it and use its results in a
process similar to what happens in modular programming
where we find functions calling each other.
• This pushed scientists to develop what we call toolsets,
which helps one to build expert systems by using higher
level building blocks. Fafner is a release of an integrated
toolset, which is available for research use.
GTs as Building Blocks (cont’d)
• Diagnosis is a problem of
finding a cause or set of
causes that “best explain”
a set of observations of a
system, some of them
indicating
behavioral
abnormality.
GTs as Building Blocks (cont’d)
• Diagnosis is a problem of
finding a cause or set of
causes that “best explain”
a set of observations of a
system, some of them
indicating
behavioral
abnormality.
• The following figure
illustrates how
integration between
various GTs can solve a
diagnosis problem.
Conclusion
• After the discovery of GTs, solution to different
kinds of problems became much easier.
›
For example, to solve a problem, a knowledge
engineer needs only choose a GT that is best suited for
performing a particular function, or can use different
GTs for performing the same function, or can use a
combination of them.
› GT facilitates knowledge acquisition because once the
KE selects the GT that he will use, his orientation while
collecting knowledge will be close to that of the GT (GT
proposes a methodology that helps in analysis, design,
and construction of a practical knowledge system).
THANK
YOU
Ihab M. Amer