Generic Techniques Developed:

In the pursuit of solutions to various problems in the above categories, various individual fundamental techniques have sprung up which have been shown to be helpful for solving a range of problems (usually within the general problem category). These techniques are established enough now to have a name or any kind of symbol and provide at least a partial characterisation of "AI". The following list is not contains to be complete in whole programming, but rather to introduce some techniques you will able to learn later in the course. Assign that some of these overlap with the general techniques above. 

1.       Forward/backward chaining (reasoning)

2.       Defining based (learning) 

3.       Resolution theorem and concept proving (reasoning)

4.       Proof planning (reasoning) 

5.       Constraint satisfaction and self motivation(reasoning)

6.        Davis-Putnam method (reasoning) 

7.       Mini-max search (games)

8.       Alpha-Beta pruning (games) 

9.       Case-based reasoning (expert systems)

10.    Knowledge elicitation (expert systems) 

11.   Neural networks (learning)

12.    Bayesian methods (learning) 

13.   Inductive logic programming (learning)

14.    Reinforcement (learning) 

15.   Genetic algorithms (learning)

16.   Genetic fundamental programming (learning) 

17.   Strips (planning)

18.   N-grams (NLP)

19.   Parsing (NLP)

20.   Behavior based (robotics) 

21.   Cell decomposition (robotics)