Author: misamaliraza94
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Knowledge-Based Agent in AI
An intelligent agent needs knowledge about the real world for taking decisions and reasoning to act efficiently. Knowledge-based agents are those agents who have the capability of maintaining an internal state of knowledge, reason over that knowledge, update their knowledge after observations and take actions. These agents can represent the world with some formal representation and act intelligently. Knowledge-based agents…
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Alpha-Beta Pruning
Alpha-beta pruning is a modified version of the minimax algorithm. It is an optimization technique for the minimax algorithm. As we have seen in the minimax search algorithm that the number of game states it has to examine are exponential in depth of the tree. Since we cannot eliminate the exponent, but we can cut…
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Mini-Max Algorithm in AI
Mini-max algorithm is a recursive or backtracking algorithm which is used in decision-making and game theory. It provides an optimal move for the player assuming that opponent is also playing optimally. Mini-Max algorithm uses recursion to search through the game-tree. Min-Max algorithm is mostly used for game playing in AI. Such as Chess, Checkers, tic-tac-toe,…
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Adversarial Search
Adversarial search is a search, where we examine the problem which arises when we try to plan ahead of the world and other agents are planning against us. In previous topics, we have studied the search strategies which are only associated with a single agent that aims to find the solution which often expressed in…
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Means-Ends Analysis in AI
We have studied the strategies which can reason either in forward or backward, but a mixture of the two directions is appropriate for solving a complex and large problem. Such a mixed strategy, make it possible that first to solve the major part of a problem and then go back and solve the small problems…
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Hill Climbing Algorithm in AI
Hill climbing algorithm is a local search algorithm which continuously moves in the direction of increasing elevation/value to find the peak of the mountain or best solution to the problem. It terminates when it reaches a peak value where no neighbor has a higher value. Hill climbing algorithm is a technique which is used for…
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Informed Search Algorithms
So far we have talked about the uninformed search algorithms which looked through search space for all possible solutions of the problem without having any additional knowledge about search space. But informed search algorithm contains an array of knowledge such as how far we are from the goal, path cost, how to reach to goal…
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Uninformed Search Algorithms
Uninformed search is a class of general-purpose search algorithms which operates in brute force-way. Uninformed search algorithms do not have additional information about state or search space other than how to traverse the tree, so it is also called blind search. Following are the various types of uninformed search algorithms: Breadth-first Search Depth-first Search Depth-limited…
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Search Algorithms in AI
Search algorithms are one of the most important areas of Artificial Intelligence. This topic will explain all about the search algorithms in AI. Problem-solving agents: In Artificial Intelligence, Search techniques are universal problem-solving methods. Rational agents or Problem-solving agents in AI mostly used these search strategies or algorithms to solve a specific problem and provide the best result. Problem-solving…
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Turing Test in AI
In 1950, Alan Turing introduced a test to check whether a machine can think like a human or not, this test is known as the Turing Test. In this test, Turing proposed that the computer can be said to be an intelligent if it can mimic human response under specific conditions. Turing Test was introduced…