We will implement a Goal-based agent (problem-solving agent) to solve problems using AI Searching Technique Uninformed Search (BFS (Breadth First Search) , DFS(Depth First Search) , Depth limited search Algorithm, Dijkstra search algorithm ) and Informed search ( Hill Climbing searc
Case study of Goal based agent through Logical and machine learning
We will implement a Goal-based agent (problem-solving agent) to solve problems using AI Searching Technique Uninformed Search (BFS (Breadth First Search) , DFS(Depth First Search) , Depth limited search Algorithm, Dijkstra search algorithm ) and Informed search ( Hill Climbing search, Best First Search, A* Algorithm, IDA* Algorithm ) . By using these algorithms we solve a problem and find a shortest path. And will conclude which one work best to solve a problem.
Project Objectives:
•To study the search algorithm.
• To compare Dijkstra, A* and IDA* using the following parameters
•· Time complexity
•· Space complexity
•· Execution time
•· With obstacle
•· Without obstacle
• To design and develop tools for pathfinding
•This section may comprise the followings;
• Building blocks you have designed and implemented.
• Procedures for testing and analysis of each of the blocks.
Technical skills upon which you have worked on
It will solve a problem more quickly and find a goal without taking time.
Solves a problem.
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