Soft Computing

Artificial Intelligence : Definitions Artificial Intelligence : Definitions  Notes
  Marvin Minsky:The science of making machines do things that would require intelligence if done by men
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Artificial Intelligence Plain and simple Artificial Intelligence Plain and simple Notes
  Artificial Intelligence is a branch of Science which deals with helping machines find solutions to complex problems in a more human-like fashion
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Artificial Intelligence Artificial Intelligence Notes
  Artificial Intelligence, or AI for short, is a combination of computer science, physiology, and philosophy. AI is a broad topic, consisting of different fields, from machine vision to expert systems. The element that the fields of AI have in common is the creation of machines that can "think".
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Steepest Descent or Gradient Method Steepest Descent or Gradient Method Notes
   Now we turn to the minimization of a function [Graphics:Images/GradientSearchMod_gr_] of n variables, where [Graphics:Images/GradientSearchMod_] and the partial derivatives of [Graphics:Images/GradientSearchMod_gr_] are accessible.
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A Definition of Soft Computing A Definition of Soft Computing Notes
  Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost.
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A Takagi-Sugeno Fuzzy Model of a Rudimentary A Takagi-Sugeno Fuzzy Model of a Rudimentary Notes
  Modern artilleries have the capability to hit targets with high level of accuracy. However, a problem arises with the current firing procedure when neither the Field Observer nor the Fire Direction Center is available to support the artillery crew with the necessary information.
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Downhill simplex Downhill simplex Notes
  The Downhill Simplex method is a multidimensional optimization method which uses geometric relationships to aid in finding function minimums
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Optimization Optimization Notes
  Unconstrained Minimization,Directional derivatives ,Minimization of Unconstrained function Steepest Descent etc.,
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Neuro-Fuzzy Modeling Neuro-Fuzzy Modeling Notes
  Model-based control schemes require the existence of a suitable process model. Proper models are, furthermore, needed to test new controllers. It is mathematically proved that the least square error (LSE) method is the optimum modeling method for linear systems [1,2].
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Kinematics and Path Planning Kinematics and Path Planning Notes
  We propose a novel solution to the problem of inverse kinematics for redundant robotic manipulators for the purposes of goal selection for path planning. We unify the calculation of the goal configuration with searching for a path in order to avoid the uncertainties inherent to selecting goal configurations which may be unreachable because they currently lie in components of the free configuration space disconnected from the initial configuration.
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Heuristic Search Heuristic Search Notes
  Direct techniques (blind search) are not always possible (they require too much time or memory). Weak techniques can be effective if applied correctly on the right kinds of tasks.
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Downhill Simplex Search Downhill Simplex Search Notes
  In multi-reference frame motion estimation (ME), the motion vector of one block can be predicted from many reference frames to improve the coding quality. Recently, a number of algorithms have been proposed to reduce the computational complexity.
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Artificial Intelligence Artificial Intelligence Notes
  The computer is interrogated by a human via a teletype, It passes if the human cannot tell if there is a computer or human at the other end
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