Artificial Intelligence
Easy Medium Difficult
2019 DEC 1. Fast Fourier transform time complexity

2. Classification algorithms

3. Min-Max algorithm

 1. Gradient descent method

2. Hill climbing algorithm

3. Dempster-Shafer theory for uncertainty

4. Additive rule model

5. Fuzzy Logic

 1. Parallelism time complexity

2. Genetic algorithm-Fitness function
2016 JUNE 1. STRIPS

2. Unsupervised Neural Network

3. Fuzzy Set Alpha cut

4. Genetic algorithms Properties

 1. Defuzzification

2. Conjunction/Disjunction

3. MIN MAX Algorithm

4. A*/Greedy best-first/Lowest cost-first

5. Fuzzy Set Alpha cut

6. Sigmoid function

7. Reinforcement learning

 1. Unsupervised algorithm(K-mean cluster)
2018  DEC 1.Propositional logic(How many models)

2.Agent

3.First order logic

 1.AND-OR Search algorithm

2.Semi-dynamic environment

3.Heuristic is admissible and heuristic is monotonous

4.Greedy BFS,A* search,Recursive BFS,Iterative-deepening A* Search)

5.Min Max game tree search

6.Propositional logic(Equivalence, Contrapositive, Converse,Implication)

—
2018  JULY 1.Environment is uncertain(deterministic/Observable)

2.Simple reflex agent

3.Propositional logic(How many models)

 1.Heuristic search algorithms

2.A* algorithm,informed search strategy

3.Propositional logic

4.First-Order Logic

5.Planning graph data structure

6.Knowledge base

7.Joint probability distribution

—