TASK DOMAIN OF AI
Areas of Artificial Intelligence
- Perception
·
Machine Vision: It is easy to interface a TV
camera to a computer and get an image
into memory; the problem is understandingwhat
the image represents. Vision takes lots
of computation; in humans, roughly 10% of all calories consumed are burned in
vision computation.
·
Speech Understanding: Speech
understanding is available now. Some systems must be trained for the individual user and require pauses between
words. Understanding continuous speech with a larger vocabulary is harder.
·
Touch(tactile or haptic) Sensation: Important for robot assembly tasks.
- Robotics Although industrial robots have been expensive, robot hardware can be
cheap: Radio Shack has sold a
working robot arm and hand for $15. The limiting factor in application of
robotics is not the cost of the robot hardware itself. What is needed is
perception and intelligence to tell the robot what to do; ``blind'' robots are
limited to very well-structured tasks (like spray painting car bodies).
-
Planning Planning attempts to order
actions to achieve goals. Planning applications include logistics, manufacturing scheduling, planning manufacturing steps
to construct a desired product. There are huge amounts of money to be saved
through better planning.
- Expert Systems Expert Systems attempt to capture the knowledge of a human expert and
make it available through a computer
program. There have been many successful and economically valuable applications
of expert systems. Expert systems provide the following benefits
• Reducing skill level needed to operate complex de vices.
• Diagnostic advice for device repair.
• Interpretation of complex data.
• ``Cloning'' of scarce expertise.
• Capturing knowledge of expert who is about to ret ire.
• Combining knowledge of multiple experts.
- Theorem Proving Proving mathematical theorems might seem to be mainly of academic
interest. However, many practical problems
can be cast in terms of theorems. A general theorem prover can therefore be
widely applicable.
Examples:
• Automatic construction of compiler code generators from a description of a CPU's instruction set.
• J Moore and colleagues proved correctness of the floating-point division
algorithm on AMD CPU chip.
- Symbolic Mathematics Symbolic mathematics refers to manipulation of formulas, rather than arithmetic on numeric values.
• Algebra
• Differential and Integral Calculus
Symbolic manipulation is often used in conjunction with ordinary
scientific computation as a generator of programs used to actually do the
calculations. Symbolic manipulation programs are an important component of
scientific and engineering workstations.
- Game Playing Games are good vehicles for research because they are well formalized,
small, and self-contained. They are
therefore easily programmed. Games can be good models of competitive
situations, so principles discovered in game-playing programs may be applicable
to practical problems.
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