Conventinal computing Conventinal computing can be thought of as a method of problem solving which ensures solution to a problem .
It produces consistent and reliable solutions following algorithm and instructions that are predefined . Conventional computing only guesses the solution without explaining and giving any reasoning. It only does what its programmed to do. It can solve one problem at a time. As they don’t learn anything it doesn’t become smart.
The processing of conventional computing is algorithmic, it does not work efficiently with rapidly changing data, hence it requires precisely stated model. Conventional computing is based on binary logic and numerical analysis. Example of conventional computing can be thought of as graphics, computer security, computational geometry(find area of geometric shapes) etc. Intelligent computing Intelligent computing can be thought of as a method of problem solving which does not guarantee a solution and the solution might not be consistent or reliable, but it is modification friendly. The processing of intelligent computing is concepts based and doesn’t require mathematical modeling. It provides reasonings and is capable of working with large and complicated problems.
Intelligent computing is based on neural networks, fuzzy logic, neural networks and intelligent agents. It can solve number of problems at a time. Example of intelligent computing can be thought of as medical diagnosis, pattern recoginition etc. Difference between Intelligent computing and Conventional computingThe difference between both are conventional computing works on set of rules and calculations, whereas intelligent computing functions on images, pictures and knowledge.Conventional computing requires exact data input and it computes sequentially , whereas inteliigent computing can deal with noisy data with parallel computing. Conventional gives precise solution whereas intelligent gives approximate answers.How to showcase a solution is intelligent or not?Intelliegrnt solution are those solution which have the capacity to solve the problem and learn from the colution.
A solution can be intelligent or not based on various parameters, how accurately is the problem solved, what extend it meets the idealized situation, using lesser resources how optimally solution is achieved. These parameters can tell us whether the solution is intelligent or not.Solutions provided by learning agent and utility agentLearning agent are those who have the ability to learn from their decisions, whereas utility agent maximize their utility function. Learning utility agent are better than utility agent when their is practical problem, when the information can be used to learn and customize the outputs according to the user.
Whereas utility agents are better than learning agents when we need to find the optimal best solution for the given problem ConclusionThe conclusion from the above report can be drawn that conventional and intelligent agent both operate on various scenarios, same the intelligent agent and the utlity agent. And intelligent solution can be obtained by both basd on the scenarios and requirements.