Knowledge is the basic element for a human brain to know and understand the things logically. When a person becomes knowledgeable about something, he is able to do that thing in a better way. In AI, the agents which copy such an element of human beings are known as knowledge-basedContinue Reading
Constraint Satisfaction Problems in Artificial Intelligence We have seen so many techniques like Local search, Adversarial search to solve different problems. The objective of every problem-solving technique is one, i.e., to find a solution to reach the goal. Although, in adversarial search and local search, there were no constraints onContinue Reading
Alpha-beta pruning is an advance version of MINIMAX algorithm. The drawback of minimax strategy is that it explores each node in the tree deeply to provide the best path among all the paths. This increases its time complexity. But as we know, the performance measure is the first consideration forContinue Reading
In artificial intelligence, minimax is a decision-making strategy under game theory, which is used to minimize the losing chances in a game and to maximize the winning chances. This strategy is also known as ‘Minmax,’ ’MM,’ or ‘Saddle point.’ Basically, it is a two-player game strategy where if one wins, the other loose the game. ThisContinue Reading
Adversarial search is a game-playing technique where the agents are surrounded by a competitive environment. A conflicting goal is given to the agents (multiagent). These agents compete with one another and try to defeat one another in order to win the game. Such conflicting goals give rise to the adversarial search. Here,Continue Reading
Difference between Intelligence and Artificial Intelligence Intelligence Artificial Intelligence It is a natural process or quality given to human beings. It is programmed using human intelligence. It is an actual hereditary. It is not hereditary but a copy of human intelligence. A human brain does not require any electricity toContinue Reading
Hill Climbing Algorithm Hill climbing search is a local search problem. The purpose of the hill climbing search is to climb a hill and reach the topmost peak/point of that hill. It is based on the heuristic search technique where the person who is climbing up on the hill estimates the direction which will leadContinue Reading
The informed and uninformed search expands the nodes systematically in two ways: keeping different paths in the memory and selecting the best suitable path, Which leads to a solution state required to reach the goal node. But beyond these “classical search algorithms,” we have some “local search algorithms” where the path costContinue Reading
Heuristic Functions As we have already seen that an informed search make use of heuristic functions in order to reach the goal node in a more prominent way. Therefore, there are several pathways in a search tree to reach the goal node from the current node. The selection of aContinue Reading
An informed search is more efficient than an uninformed search because in informed search, along with the current state information, some additional information is also present, which make it easy to reach the goal state. Below we have discussed different types of informed search: Best-first Search (Greedy search) A best-firstContinue Reading
You cannot copy content of this page
WhatsApp us