Skip to main content

Featured post

A* ALGORITHM BASICS FOR PATH FINDING & HEURISTICS METHODS : ARTIFICIAL INTELLIGENCE

By
 A* ALGORITHM BASICS FOR PATH FINDING A* , widely used  known form of best-first search & path planning algorithm nowadays in mobile robots,games. this is the function for A*,                                     f(n) = g(n) + h(n) g ( n ) is the cost of the path from the start node to n , and h ( n ) is a heuristic function that estimates the cost of the cheapest path from n to the goal This will find cheapest f(n) value in neighbor nodes to archive goal node. check below image  A to B path finding with g(n),h(n),f(n) value In the final level check below image Now we will check the Algorithm // A* Search Algorithm 1. Initialize the open list 2. Initialize the closed list put the starting node on the open list (you can leave its f at zero) 3. ...
6 comments

BACKTRACKING ALGORITHM FOR THE N QUEENS PROBLEM & PYTHON IMPLEMENTATION: ARTIFICIAL INTELLIGENCE

By
 ALGORITHM

The problem is to place n queens on an n * n chessboard, so that no two queens are attacking each other.this means that no two queens are in the same row, the same column, or the same diagonal.


This is the algorithm for n queens backtracking :

PLACEQUEENS(Q[1..N],r):
       if r=n+1
            print Q[1...n]
       else
            for j <-- 1 to n
                 legal <--- TRUE
                 for i <-- 1 to r-1
                      if (Q[i]=j) or (Q[i]=j+r-i) or (Q[i] =j-r+i)  :
                                 legal <-- FALSE
                 
                 if legal
                         Q[r] <-- j
                         PLACEQUEENS(Q[1..N],r+1)   //recursion

Here represent the positions of the queens using an array Q[1 .. n], where Q[i] indicates which square in row i contains a queen. When backtrack is called, the input parameter r is the index of the first empty row, and the prefix Q[1 .. r 1] contains the positions of the first r-1 queens. In particular, to compute all n-queens solutions with no restrictions, we would call backtrack (Q[1 .. n], 1). The outer for-loop considers all possible placements of a queen on row r; the inner for-loop checks whether a candidate placement of row r is consistent with the queens that are already on the first r 1 rows

PYTHON IMPLEMENTATION
  
Just  download python script through below github link & run it
BACKTRACKING-ALGORITHM-PYTHON

 check below Demo

Comments

Post a Comment

Popular posts from this blog

Getting Started with ARGoS Large-Scale Swarm Robot Simulator in Ubuntu

By
ARGoS (Autonomous Robots Go Swarming) is a multi-robot simulator designed to support large teams of robots. Its design is pretty different from the design of other simulators. Its most distinctive feature is that the 3D simulated world can be divided in regions, and each region can be assigned to a different physics engine. Furthermore, ARGoS' design revolves around the concept of tunable accuracy. In other words, in ARGoS, everything is a plug-in (robot models, sensors, actuators, physics engines, visualisations, etc) and the user can select which plug-ins to use for an experiment.  Since different plug-ins have different accuracy and computational costs, users can choose which plug-ins to use for each aspect of the simulation and assign resources only where it matters. This makes the simulation as fast as possible. At the time of writing, ARGoS supports the Swarmanoid robots (foot-bot and eye-bot) and the e-puck. ARGoS supports Linux and Mac OSX. Binary packages are availa...
Post a Comment
Read more

A* ALGORITHM BASICS FOR PATH FINDING & HEURISTICS METHODS : ARTIFICIAL INTELLIGENCE

By
 A* ALGORITHM BASICS FOR PATH FINDING A* , widely used  known form of best-first search & path planning algorithm nowadays in mobile robots,games. this is the function for A*,                                     f(n) = g(n) + h(n) g ( n ) is the cost of the path from the start node to n , and h ( n ) is a heuristic function that estimates the cost of the cheapest path from n to the goal This will find cheapest f(n) value in neighbor nodes to archive goal node. check below image  A to B path finding with g(n),h(n),f(n) value In the final level check below image Now we will check the Algorithm // A* Search Algorithm 1. Initialize the open list 2. Initialize the closed list put the starting node on the open list (you can leave its f at zero) 3. ...
6 comments
Read more

Ros Topics : Ros Tutorial

By
Topics , Its look like pipe line connection between two or more nodes,This is the way to transfer data continuously within two nodes.    Each message in ROS is transported using named buses called topics. When a node sends a message through a topic, then we can say the node is publishing a topic. When a node receives a message through a topic, then we can say that the node is subscribing to a topic. The publishing node and subscribing node are not aware of each other's existence. We can even subscribe a topic that might not have any publisher. In short, the production of information and consumption of it are decoupled. Each topic has a unique name, and any node can access this topic and send data through it as long as  they have the right message type Ros topic have two types of method   1. topic publisher   2. topic subscriber  ROS has a tool to work with topics called rostopic . It is a command-line tool that gives us information abo...
Post a Comment
Read more

Translate