Conventional how to solve a given problem Series

                                Conventional vs Intelligent ComputingConventional computing is a traditional way of computing by which we can get guaranteed solution to a given problem.Results produced are consistent, reliable and solves given problem according to programmer’s instruction or algorithm.   Problem is treated with rigorous mathematical analysis   Mathematical models are created based on mathematical formulas  We can analyze computing technique mathematically   Follows sequential processing, One problem can be solved at a given time.  Programmer gives instruction to a system on how to solve a given problem  Program Doesn’t have reasoning capability            Intelligent computing is a way of computing which doesn’t guarantee a solution to a given problem.Results produced may not be reliable or consistent and will solve the given problem without program instruction.    Programmer doesn’t give instruction to a system on how to solve a given problem   Series of problems can be solved at a given time    Based on rules, conceptualization and reasoning so system has reasoning capability       Intelligent computing is used mainly for complex real-world problems where using traditional methods (conventional computing) is not easy or useless as the process might be too complex for using conventional mathematical methods.In Traditional approach, we build mathematical models or use if-then-else. Example: – Brute-Force method is used to solve a problem of chess but this approach is expensive, ineffective and may arrive at poor solutions. For this type of problem using Intelligent computing is far better as methods used in intelligent computing are very close to human’s way of reasoning and thus it is a way of performing like humans.Intelligent computing arrives at a solution for a problem by using models of how living beings such as human beings, ants etc. will solve a given problem.Intelligent computing has been used exponentially over the past few years as intelligent techniques and it is tolerant of imprecision and uncertainty and are tractable, robust and effective.A solution is said to be intelligent if it has a:-Ability to solve new problems.Ability to learn and grow.Ability to act like humans.Ability to interact with the real world.Ability to reason & plan.Ability to adapt to changing environment.Agents are the entities which observes through sensors and act on the environment and performs the activity which helps in achieving goals.It is capable of generating action and action depends on most recent perception.Types of Agent:Learning Agent-By learning, agents acquire the capability of competence by observation, actions.Learning agent gains feedback from the critic on how well it is performing and what should be done to improve its performance.Four components in learning agents are:Critic.Learning element.Problem generator.Performance Element.Utility Agent-Utility based agents define a measure of how desirable a particular state is and it is obtained through the use of a utility function.Conclusion: Conventional computing has its limitations and to make computation fast and effective we need “intelligent”   abilities in systems so that they can think, behave and reason just like humans.