To design and implement different techniques to develop simple autonomous agents that make
effective decisions in fully informed, and partially observable, settings.
To apply appropriate algorithms for solving given AI problems.
To Design and implement logical reasoning agents.
To Design and implement agents that can reason under uncertainty.
To understand the Implementation of these reasoning systems using either backward or
forward inference mechanisms
LIST OF EXPERIMENTS:
Develop PEAS descriptions for given AI tasks
Implement basic search strategies for selected AI applications
Implement A* and memory bounded A* algorithms
Implement genetic algorithms for AI tasks
Implement simulated annealing algorithms for AI tasks
Implement alpha-beta tree search
Implement backtracking algorithms for CSP
Implement local search algorithms for CSP
Implement propositional logic inferences for AI tasks
Implement resolution based first order logic inferences for AI tasks
Implement classical planning algorithms
Mini-Project
COURSE OUTCOMES
Implement simple PEAS descriptions for given AI tasks
Develop programs to implement simulated annealing and genetic algorithms
Demonstrate the ability to solve problems using searching and backtracking
Ability to Implement simple reasoning systems using either backward or forward inference
mechanisms
Will be able to choose and implement a suitable technics for a given AI task
SOFTWARE:
C++ or Java Software
About
This folder contains all the search algorithm which is used in Artificial Intelligence field.