Tech Differences

In Artificial intelligence, the purpose of the search is to find the path through a problem space. There are two ways to pursue such a search that are forward and backward reasoning. The significant difference between forward and backward reasoning is that forward reasoning starts with the initial data towards the goal. Conversely, backward reasoning works in opposite fashion where the purpose is to determine the initial facts and information with the help of the given results. Content: Forward … [Read more...]

Searching is a process of finding a sequence of steps needed to solve any problem. The prior difference between informed and uninformed search is that the informed search provides the guidance on where and how to find the solution. Conversely, the uninformed search gives no additional information about the problem except its specification. However, between both informed and uninformed search techniques, the informed search is more efficient and cost-effective. Content: Informed Search Vs … [Read more...]

Supervised and Unsupervised learning are the machine learning paradigms which are used in solving the class of tasks by learning from the experience and performance measure. The supervised and Unsupervised learning mainly differ by the fact that supervised learning involves the mapping from the input to the essential output. On the contrary, unsupervised learning does not aim to produce output in the response of the particular input instead it discovers patterns in data. These supervised and … [Read more...]

Fuzzy set and crisp set are the part of the distinct set theories, where the fuzzy set implements infinite-valued logic while crisp set employs bi-valued logic. Previously, expert system principles were formulated premised on Boolean logic where crisp sets are used. But then scientists argued that human thinking does not always follow crisp "yes"/"no" logic, and it could be vague, qualitative, uncertain, imprecise or fuzzy in nature. This gave commencement to the development of the fuzzy set … [Read more...]

Soft computing and hard computing are computing methods where hard computing is the conventional methodology relies on the principles of accuracy, certainty, and inflexibility. Conversely, soft computing is a modern approach premised on the idea of the approximation, uncertainty, and flexibility. Before understanding soft computing and hard computing we should understand, what is computing? The computing in terms of computer technology is the process of accomplishing the particular task with … [Read more...]