Artificial Intelligence: Introduction, Typical Applications. State Space Search: Depth Bounded DFS, Depth First Iterative Deepening. Heuristic Search: Heuristic Functions, Best First Search, Hill Climbing, Variable Neighborhood Descent, Beam Search, Tabu Search. Optimal Search: A * algorithm, Iterative Deepening A* , Recursive Best First Search, Pruning the CLOSED and OPEN Lists

1. Topic To Be Covered:
State Space Search in ai
Jagdamba Education Society's
SND College of Engineering & Research Centre
Department of Computer Engineering
SUBJECT: Artificial Intelligence & Robotics
Lecture No-04
Prof.Dhakane Vikas N

2. AI in gaming
 In video games, artificial intelligence (AI) is used to generate responsive,
adaptive or intelligent behaviors primarily in non-player characters
(NPCs) similar to human-like intelligence.
 Artificial intelligence has been an integral part of video games since their
inception in the 1950s.

3. AI in gaming
 AlphaGO-AlphaZero- Alpha Go defeated the European Go champion Fan
Hui, professional, five to zero. This was the first time a computer Go
program had beaten a professional human player on a full-sized board.
 IBM's computer Deep Blue beat world chess champion Garry Kasparov in
the 1997 match

4. AI in gaming
 Alpha Go and its successors use a Monte Carlo tree search algorithm to
find its moves based on knowledge previously "learned" by machine
learning, specifically by an artificial neural network (a deep
learning method) by extensive training, both from human and computer
play.

5. Problem solving in ai: state space search
Artificial Intelligence as a problem
solver
 According to Computer science most
important part of Artificial intelligence is
problem solving which can be done by
using various techniques and algorithms
of AI.
 Ex: STATE SPACE SEARCH
 The aim of Artificial Intelligence is to
develop a system which can solve the
various problems on its own.
 Various applications of AI are nothing but
satisfying some constraints(Finding
solution) to various kinds of real world
problems.

6. Problem solving in ai: state space search
state space search
 SSS is the most commonly used
technique in AI for problem solving
 In, general searching refers to as
finding information one needs.
 STATE SPACE
 The state space of a problem is the set
of all states reachable from initial
state by executing any sequence of
actions.
 State space specifies the relation
among various problems sates thereby
forming directed network of graphs in
which the nodes are states and the
links between nodes represent actions.

7. Problem solving in ai: state space search
state space search
 State space search: It is searching in
given space of states pertaining to a
problem under consideration.
 State space search: is a process
used in the field of computer science,
including artificial intelligence
(AI), in which successive
configurations or states of an instance
are considered, with the intention of
finding a goal state with a desired
property.
 Path: A path is sequence of states
connected by sequence of actions, in a
given state space.

8. Problem solving in ai: state space search
Properties of search algorithm
I. Completeness
A search is said to be complete if it guarantee to return a at least one
solution for any random input.
II. Optimality
Id a solution found using algorithm is guarantee to be the best
solution(lowest path cost) among all other solutions then such solution is
called optimal solution.
III. Time Complexity
It is the measure of the time for an algorithm to complete its task.
IV. Space Complexity
It is maximum storage required at any point during the search as the
complexity of problem.