Knowledge Based Agents in AI
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…
Cryptarithmetic Problem in AI
Cryptarithmetic Problem is a type of constraint satisfaction problem where the game is about digits and its unique replacement either with alphabets or other symbols. In cryptarithmetic problem, the digits (0-9) get substituted by…
Problem Solving in Artificial Intelligence
The reflex agent of AI directly maps states into action. Whenever these agents fail to operate in an environment where the state of mapping is too large and not easily…
Constraint Satisfaction Problems in Artificial Intelligence
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.,…
Alpha-beta Pruning in Artificial Intelligence
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…
Minimax Strategy
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…
Adversarial Search in Artificial Intelligence
AI Adversarial search: 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…
Differences in Artificial Intelligence
Difference between Intelligence and Artificial Intelligence IntelligenceArtificial IntelligenceIt 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…
Hill Climbing Algorithm in AI
State-space Landscape of Hill climbing algorithm To understand the concept of hill climbing algorithm, consider the below landscape representing the goal state/peak and the current state of the climber. The topographical regions shown in…
Local Search Algorithms and Optimization Problem
The informed and uninformed search expands the nodes systematically in two ways: keeping different paths in the memory andselecting the best suitable path, Which leads to a solution state required to reach the goal…
