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Unit 14: Knowledge-based Decision Support




          We need learning not just for erudition, but because having a better idea of how the world  Notes
          works enables us to generate more effective strategies for dealing with it. We need visual
          perception not just because seeing is fun, but in order to get a better idea of what an action might
          achieve.

          14.1.2 Areas of Artificial Intelligence

          Various application areas of artificial intelligence are:

               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 devices.
                    Diagnostic advice for device repair.

                    Interpretation of complex data.
                    “Cloning” of scarce expertise.
                    Capturing knowledge of expert who is about to retire.
                    Combining knowledge of multiple experts.
                    Intelligent training.

               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.

                 Example:

                    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.




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