This is a presentation slide of our project, which is made by C programming language. our project topic was Tic tac Toe game. this is a mini-game project .
A light-emitting diode (LED) is a semiconductor device that emits visible light when an electric current passes through it. LEDs have several advantages over traditional light sources like incandescent bulbs including higher energy efficiency, longer lifetime, resistance to shock, and ability to emit light in specific wavelengths. However, LEDs also have some disadvantages like higher initial cost and sensitivity to temperature changes.
This document discusses cyber security and cyber crimes. It defines cyber security as technologies and practices to protect networks and data from unauthorized access and cyber crimes as criminal activities carried out using computers or networks. The document describes common cyber attacks like man-in-the-middle attacks, DDoS attacks, SQL injection, and phishing. It also discusses preventive security measures and advantages of cyber security like protecting against viruses and data theft. The conclusion is that cyber crimes cannot be fully stopped but cyber security can help prevent them.
This document discusses the development of a Tic Tac Toe game in Java using NetBeans. It introduces the students who created the project and provides an overview of the Java programming language. It then describes the key aspects of the project, including using a 3x3 matrix to represent the game board, allowing a user to play against the computer, and outlining the constructor, game turn logic, and drawing methods. The summary concludes with an example of game play where the computer takes the first turn, then the players take alternating turns until the user wins the game.
This document discusses three programs of increasing complexity for playing Tic-Tac-Toe against an AI opponent. Program 1 stores all possible board configurations in a large table, but requires significant storage. Program 2 uses functions to evaluate the board and make strategic moves to win or block opponents, but cannot generalize to 3D games. Program 3 represents the board as structures containing possible future moves rated by likelihood of winning, allowing it to look ahead multiple turns and generalize better to more complex games.
The document discusses the random forest algorithm. It introduces random forest as a supervised classification algorithm that builds multiple decision trees and merges them to provide a more accurate and stable prediction. It then provides an example pseudocode that randomly selects features to calculate the best split points to build decision trees, repeating the process to create a forest of trees. The document notes key advantages of random forest are that it avoids overfitting and can be used for both classification and regression tasks.
This document discusses different logic families including Resistor Transistor Logic (RTL), Diode Transistor Logic (DTL), Transistor-Transistor Logic (TTL), and Emitter Coupled Logic (ECL). It provides circuit diagrams and explanations of the working principles for each logic family. Key characteristics like fan-in, fan-out, propagation delay, noise immunity, and power dissipation are compared for each logic family.
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , disadvantages , benefits , applications .
We hope it to be useful .
1. The document describes an artificial intelligence implementation of the tic-tac-toe game using the minimax algorithm.
2. It provides details on the game rules, initial and goal states, and the state space tree and winning conditions.
3. The minimax approach is then explained as a recursive algorithm that evaluates all possible future moves from the current state and assumes the opponent will make the choice that results in the least preferred outcome.
The document describes a Python program that allows users to play Tic-Tac-Toe against the computer. The program uses a command line interface to display a 3x3 grid where users can place an 'X' or 'O' by entering a number 1-9. The program determines whose turn it is, checks for a win or draw after each turn, and repeats the game without errors. It was created using the Python programming language, Python 3.6 interpreter, and Atom text editor on an Intel processor with 512MB of memory. Potential future improvements include a graphical user interface, multiplayer mode, and difficulty levels.
This document describes the development of a Tic Tac Toe Android application using the minimax algorithm. It provides background on Android, artificial intelligence, and the minimax algorithm. The goals are to learn object-oriented programming, Android development, and implement the minimax algorithm to make the computer player more intelligent in Tic Tac Toe. The application will allow single-player against the computer and multi-player between two devices.
This document appears to be a project report for a summer internship developing a Tic Tac Toe game app. It includes an introduction describing the objectives of creating an efficient app to teach the game. It provides code snippets for the game logic and user interface. It also includes diagrams of the data flow and use cases. The report describes further enhancements that could be made, such as additional modes and improved graphics. It indicates testing was done to validate the game mechanics work as intended.
- Tic-tac-toe is a paper-and-pencil game where two players alternate placing Xs and Os on a 3x3 grid. The first player to get 3 in a row wins.
- The game uses a 3x3 character matrix to represent the board, and functions like check() to evaluate the board state after each move.
- The get_computer_move() function uses minimax search to evaluate all possible future moves and choose the move that maximizes the computer's chance of winning or drawing. It simulates both players' optimal play to assign each possible current move a grade.
This document presents a C++ program for a Tic Tac Toe game. It includes an introduction to the game and C++ language. The program structure is explained including initializing variables, displaying the game board, getting player moves, and checking for a winner or draw. Code snippets are provided to demonstrate how player turns are handled, valid moves checked, and the different ways the game can end. Screenshots of game play are also included to illustrate an invalid move and a draw result.
The document describes a Tic Tac Toe game program written in C++. It includes sections on system requirements, coding, and output. The program initializes variables like a character array to represent the game board. It then enters a main game loop where it displays the board, gets a player's move, and checks for a winner or draw after each turn. If an invalid move is made, the player is prompted to try again. After the game ends, it displays the final board and announces the winner or a draw.
This document describes how to program simple AI for a Tic-Tac-Toe game by building a game tree to represent all possible game configurations and selecting the move that yields the best outcome. It explains that the game tree will have MAX and MIN nodes to represent whose turn it is, and children nodes for each possible move. The algorithm searches the tree to a depth of 2, then the root node selects the move with the highest evaluation value to determine the computer's best move.
The document describes a Tic-Tac-Toe game project created with graphics. It includes a 3x3 grid where two players take turns placing X's and O's to try and get 3 in a row. It explains the game functions like displaying the board, checking for a winner or draw, and ending the game. It also shows the game interface and thanks the viewer for watching the presentation.
BackTracking Algorithm: Technique and ExamplesFahim Ferdous
This slides gives a strong overview of backtracking algorithm. How it came and general approaches of the techniques. Also some well-known problem and solution of backtracking algorithm.
The document presents a logic puzzle about a monkey trying to reach bananas hung from the ceiling. It describes the problem setup, with a monkey and bananas in a room, along with a chair. It then provides the logical representation of the problem using predicates and axioms. The goal is to use resolution logic to prove that the monkey can reach the bananas by placing the chair below them and climbing on top of it. Through a series of resolvents applying the given information, it is shown that the monkey can indeed reach the bananas.
This document summarizes the development of a Tic Tac Toe game with different features and levels of difficulty. It describes how the original 3x3 game was expanded to a 4x4 version, and how single-player modes against the computer were implemented. Players can now select between Easy, Medium, and Hard difficulty levels when playing against the CPU. The development process involved understanding the original code, expanding the board size, modifying the winning conditions, adding CPU logic, and implementing a difficulty selection system.
Computer graphics lab report with code in cppAlamgir Hossain
This is the lab report for computer graphics in cpp language. Basically this course is only for the computer science and engineering students.
Problem list:
1.Program for the generation of Bresenham Line Drawing.
2. Program for the generation of Digital Differential Analyzer (DDA) Line Drawing.
3. Program for the generation of Midpoint Circle Drawing.
4. Program for the generation of Midpoint Ellipse Drawing.
5. Program for the generation of Translating an object.
6. Program for the generation of Rotating an Object.
7. Program for the generation of scaling an object.
All programs are coaded in cpp language .
The document discusses game playing in artificial intelligence. It describes how general game playing (GGP) involves designing AI that can play multiple games by learning the rules, rather than being programmed for a specific game. The document outlines how the minimax algorithm is commonly used for game playing, involving move generation and static evaluation functions to search game trees and determine the best move by maximizing or minimizing values at each level.
Problem solving
Problem formulation
Search Techniques for Artificial Intelligence
Classification of AI searching Strategies
What is Search strategy ?
Defining a Search Problem
State Space Graph versus Search Trees
Graph vs. Tree
Problem Solving by Search
This document summarizes a C++ program for a Tic Tac Toe game presented by a group of students. It begins with an introduction to the game of Tic Tac Toe and an overview of how the program works. The program uses variables to initialize the game board and track turns. It has a main game loop that displays the board, gets player moves, and checks for a winner or draw after each turn. Several members of the group then present code segments in more detail, including initializing variables, the game loops, validating player moves, checking win conditions, and asking the user to play again or quit.
The document discusses the greedy method algorithmic approach. It provides an overview of greedy algorithms including that they make locally optimal choices at each step to find a global optimal solution. The document also provides examples of problems that can be solved using greedy methods like job sequencing, the knapsack problem, finding minimum spanning trees, and single source shortest paths. It summarizes control flow and applications of greedy algorithms.
This document presents an overview of the Floyd-Warshall algorithm. It begins with an introduction to the algorithm, explaining that it finds shortest paths in a weighted graph with positive or negative edge weights. It then discusses the history and naming of the algorithm, attributed to researchers in the 1950s and 1960s. The document proceeds to provide an example of how the algorithm works, showing the distance and sequence tables that are updated over multiple iterations to find shortest paths between all pairs of vertices. It concludes with discussing the time and space complexity, applications, and references.
Conceptual Dependency (CD) is a theory developed by Schank in the 1970s to represent the meaning of natural language sentences using conceptual primitives rather than words. CD representations are built using primitives that capture the intended meaning, are language independent, and help draw inferences. There are different primitive actions, conceptual categories, and rules to build CD representations from sentences. While CD provides a general model for knowledge representation, it can be difficult to construct original sentences from representations and represent complex actions without many primitives.
This document discusses adversarial search in artificial intelligence. It provides an overview of games and introduces the minimax algorithm. The minimax algorithm is used to determine optimal strategies in two-player adversarial games by recursively considering all possible moves by both players. Tic-tac-toe is given as an example game where minimax can be applied to choose the best first move. The properties and limitations of the minimax algorithm are also summarized.
The document describes an Android application for playing Tic-Tac-Toe against an AI. It includes a description of the game and strategy, as well as the application's design, user interface, algorithms, and technologies used including Java, XML, and Android SDK. The application tracks scores over multiple games and allows both single-player against the AI and two-player modes.
The document describes a rule-based expert system for playing the game of 5x5x5 Tic-Tac-Toe (Quintic). It discusses researching the 3x3 game and adapting those rules for Quintic. The system divides the game into beginning, middle, and end states and defines rules for each, prioritizing moves that create winning lines or block opponent's lines. The system represents the 3D board as an array and defines the value of each position based on the number of winning lines it interacts with.
1. The document describes an artificial intelligence implementation of the tic-tac-toe game using the minimax algorithm.
2. It provides details on the game rules, initial and goal states, and the state space tree and winning conditions.
3. The minimax approach is then explained as a recursive algorithm that evaluates all possible future moves from the current state and assumes the opponent will make the choice that results in the least preferred outcome.
The document describes a Python program that allows users to play Tic-Tac-Toe against the computer. The program uses a command line interface to display a 3x3 grid where users can place an 'X' or 'O' by entering a number 1-9. The program determines whose turn it is, checks for a win or draw after each turn, and repeats the game without errors. It was created using the Python programming language, Python 3.6 interpreter, and Atom text editor on an Intel processor with 512MB of memory. Potential future improvements include a graphical user interface, multiplayer mode, and difficulty levels.
This document describes the development of a Tic Tac Toe Android application using the minimax algorithm. It provides background on Android, artificial intelligence, and the minimax algorithm. The goals are to learn object-oriented programming, Android development, and implement the minimax algorithm to make the computer player more intelligent in Tic Tac Toe. The application will allow single-player against the computer and multi-player between two devices.
This document appears to be a project report for a summer internship developing a Tic Tac Toe game app. It includes an introduction describing the objectives of creating an efficient app to teach the game. It provides code snippets for the game logic and user interface. It also includes diagrams of the data flow and use cases. The report describes further enhancements that could be made, such as additional modes and improved graphics. It indicates testing was done to validate the game mechanics work as intended.
- Tic-tac-toe is a paper-and-pencil game where two players alternate placing Xs and Os on a 3x3 grid. The first player to get 3 in a row wins.
- The game uses a 3x3 character matrix to represent the board, and functions like check() to evaluate the board state after each move.
- The get_computer_move() function uses minimax search to evaluate all possible future moves and choose the move that maximizes the computer's chance of winning or drawing. It simulates both players' optimal play to assign each possible current move a grade.
This document presents a C++ program for a Tic Tac Toe game. It includes an introduction to the game and C++ language. The program structure is explained including initializing variables, displaying the game board, getting player moves, and checking for a winner or draw. Code snippets are provided to demonstrate how player turns are handled, valid moves checked, and the different ways the game can end. Screenshots of game play are also included to illustrate an invalid move and a draw result.
The document describes a Tic Tac Toe game program written in C++. It includes sections on system requirements, coding, and output. The program initializes variables like a character array to represent the game board. It then enters a main game loop where it displays the board, gets a player's move, and checks for a winner or draw after each turn. If an invalid move is made, the player is prompted to try again. After the game ends, it displays the final board and announces the winner or a draw.
This document describes how to program simple AI for a Tic-Tac-Toe game by building a game tree to represent all possible game configurations and selecting the move that yields the best outcome. It explains that the game tree will have MAX and MIN nodes to represent whose turn it is, and children nodes for each possible move. The algorithm searches the tree to a depth of 2, then the root node selects the move with the highest evaluation value to determine the computer's best move.
The document describes a Tic-Tac-Toe game project created with graphics. It includes a 3x3 grid where two players take turns placing X's and O's to try and get 3 in a row. It explains the game functions like displaying the board, checking for a winner or draw, and ending the game. It also shows the game interface and thanks the viewer for watching the presentation.
BackTracking Algorithm: Technique and ExamplesFahim Ferdous
This slides gives a strong overview of backtracking algorithm. How it came and general approaches of the techniques. Also some well-known problem and solution of backtracking algorithm.
The document presents a logic puzzle about a monkey trying to reach bananas hung from the ceiling. It describes the problem setup, with a monkey and bananas in a room, along with a chair. It then provides the logical representation of the problem using predicates and axioms. The goal is to use resolution logic to prove that the monkey can reach the bananas by placing the chair below them and climbing on top of it. Through a series of resolvents applying the given information, it is shown that the monkey can indeed reach the bananas.
This document summarizes the development of a Tic Tac Toe game with different features and levels of difficulty. It describes how the original 3x3 game was expanded to a 4x4 version, and how single-player modes against the computer were implemented. Players can now select between Easy, Medium, and Hard difficulty levels when playing against the CPU. The development process involved understanding the original code, expanding the board size, modifying the winning conditions, adding CPU logic, and implementing a difficulty selection system.
Computer graphics lab report with code in cppAlamgir Hossain
This is the lab report for computer graphics in cpp language. Basically this course is only for the computer science and engineering students.
Problem list:
1.Program for the generation of Bresenham Line Drawing.
2. Program for the generation of Digital Differential Analyzer (DDA) Line Drawing.
3. Program for the generation of Midpoint Circle Drawing.
4. Program for the generation of Midpoint Ellipse Drawing.
5. Program for the generation of Translating an object.
6. Program for the generation of Rotating an Object.
7. Program for the generation of scaling an object.
All programs are coaded in cpp language .
The document discusses game playing in artificial intelligence. It describes how general game playing (GGP) involves designing AI that can play multiple games by learning the rules, rather than being programmed for a specific game. The document outlines how the minimax algorithm is commonly used for game playing, involving move generation and static evaluation functions to search game trees and determine the best move by maximizing or minimizing values at each level.
Problem solving
Problem formulation
Search Techniques for Artificial Intelligence
Classification of AI searching Strategies
What is Search strategy ?
Defining a Search Problem
State Space Graph versus Search Trees
Graph vs. Tree
Problem Solving by Search
This document summarizes a C++ program for a Tic Tac Toe game presented by a group of students. It begins with an introduction to the game of Tic Tac Toe and an overview of how the program works. The program uses variables to initialize the game board and track turns. It has a main game loop that displays the board, gets player moves, and checks for a winner or draw after each turn. Several members of the group then present code segments in more detail, including initializing variables, the game loops, validating player moves, checking win conditions, and asking the user to play again or quit.
The document discusses the greedy method algorithmic approach. It provides an overview of greedy algorithms including that they make locally optimal choices at each step to find a global optimal solution. The document also provides examples of problems that can be solved using greedy methods like job sequencing, the knapsack problem, finding minimum spanning trees, and single source shortest paths. It summarizes control flow and applications of greedy algorithms.
This document presents an overview of the Floyd-Warshall algorithm. It begins with an introduction to the algorithm, explaining that it finds shortest paths in a weighted graph with positive or negative edge weights. It then discusses the history and naming of the algorithm, attributed to researchers in the 1950s and 1960s. The document proceeds to provide an example of how the algorithm works, showing the distance and sequence tables that are updated over multiple iterations to find shortest paths between all pairs of vertices. It concludes with discussing the time and space complexity, applications, and references.
Conceptual Dependency (CD) is a theory developed by Schank in the 1970s to represent the meaning of natural language sentences using conceptual primitives rather than words. CD representations are built using primitives that capture the intended meaning, are language independent, and help draw inferences. There are different primitive actions, conceptual categories, and rules to build CD representations from sentences. While CD provides a general model for knowledge representation, it can be difficult to construct original sentences from representations and represent complex actions without many primitives.
This document discusses adversarial search in artificial intelligence. It provides an overview of games and introduces the minimax algorithm. The minimax algorithm is used to determine optimal strategies in two-player adversarial games by recursively considering all possible moves by both players. Tic-tac-toe is given as an example game where minimax can be applied to choose the best first move. The properties and limitations of the minimax algorithm are also summarized.
The document describes an Android application for playing Tic-Tac-Toe against an AI. It includes a description of the game and strategy, as well as the application's design, user interface, algorithms, and technologies used including Java, XML, and Android SDK. The application tracks scores over multiple games and allows both single-player against the AI and two-player modes.
The document describes a rule-based expert system for playing the game of 5x5x5 Tic-Tac-Toe (Quintic). It discusses researching the 3x3 game and adapting those rules for Quintic. The system divides the game into beginning, middle, and end states and defines rules for each, prioritizing moves that create winning lines or block opponent's lines. The system represents the 3D board as an array and defines the value of each position based on the number of winning lines it interacts with.
The document describes the game of Tic Tac Toe and how to code it. It is divided into 3 sections - an introduction to how the game is played, an algorithm for the game logic, and Python code with explanations. The code creates a Tic Tac Toe board class with methods for placing markers, checking for wins/draws, and starting the game. It randomly selects the first player and alternates turns until the game ends.
The document provides an introduction and overview of AlphaGo Zero, including:
- AlphaGo Zero achieved superhuman performance at Go without human data by using self-play reinforcement learning.
- It uses a policy network and Monte Carlo tree search to select moves. The network is trained through self-play games using its own policy and value outputs as training labels.
- Experiments showed AlphaGo Zero outperformed previous AlphaGo versions and human-trained networks, and continued improving with deeper networks and more self-play training.
0-miniproject sem 4 review 1(1)(2).pptxAhishektttPhm
This document discusses implementing tic-tac-toe in Python using the minimax algorithm. It begins with prerequisites including Python, the game, and the minimax algorithm. It then covers strategies for playing optimally such as blocking forks and playing the center. The minimax algorithm is explained as exploring the game tree and assigning scores. Pseudocode is provided for the architecture. The code implementation includes displaying the board, playing, and checking for wins or ties. Applications are given like game shows based on tic-tac-toe. Limitations are it can only be two players without levels. References are provided.
1. Game playing is an important domain for artificial intelligence research as games provide formal reasoning problems that allow direct comparison between computer programs and humans.
2. Alpha-beta pruning can speed up minimax search in game trees by pruning branches that cannot alter the outcome. It works by maintaining lower and upper bounds on the score.
3. Evaluating leaf nodes is challenging. For chess, linear evaluation functions combining weighted features like material and position are commonly used, and reinforcement learning can help tune the weights.
Study on Evaluation Function Design of Mahjong using Supervised Learningharmonylab
1) This study used supervised learning and deep learning methods to design an evaluation function for playing mahjong, an imperfect information game with uncertainty and randomness.
2) Several neural networks were created to predict game states like whether opponents are waiting and which tiles they may be waiting for, and to determine the best tile to discard.
3) Experiments showed the deep learning model had a better win and placement rate than a baseline algorithm, taking more aggressive moves while still prioritizing defense when needed. The model played more like human players.
The document provides instructions for building a Tic Tac Toe game in JavaScript. It introduces key JavaScript concepts like variables, arrays, functions, objects and loops that will be used to track game state and logic. Challenges are presented throughout for readers to practice applying the concepts, like setting up variables to track wins and whose turn it is. The goal is to create an interactive game that displays an X or O with each player's click and checks for a winner or tie after each turn.
Video and related blog posts at fsharpforfunandprofit.com/ettt
Follow along as I ridiculously over-engineer a simple game to demonstrate how functional programming can be used to create a real-world "enterprise-ready" application.
Topics covered include: encoding business rules into types, data hiding with parametric polymorphism, using functions for capability-based security, exposing a REST API with HATEAOS, the functional approach to logging, actors, scalability and more.
This is an individual project, to be completed on your own. It i.docxabhi353063
This is an
individual
project, to be completed on your own. It is considered dishonest either to read someone else's solution or to provide a classmate with a copy of your work. Do not make the mistake of thinking that superficial changes in a program (such as altering comments, changing variable names, or interchanging statements) can be used to avoid detection. If you cannot do the work yourself, it is extremely unlikely that you can succeed in disguising someone else's work. We are adamant that cheating in any form is not tolerated. Even the most trivial assignment is better not done than if you cheat to complete it.
Prerequisites
Primitive types
Conditionals
Loops
Arrays
Learning Objectives
Problem Solving
Traversing and manipulating 2-dimensional arrays
Using nested loops
Introduction
In this project, you will implement the logic of the game
Othello
, also known as
Reversi
.
Game Rules
Othello is a strategy board game for two players on a squared checkered board. It is played with identical disks that are white on one side and black on the other. Players take turns placing disks on the board with their assigned color facing up.
The game starts with four disks placed in a square at the center of the board in a standard diagonal pattern: two facing white side up, two facing black side up and same-colored disk on a diagonal with each other. These four initial disks are
not
placed by the player.
The black player moves first. He must place a disk with the black side up on the board, in such a position that there exists
at least
one straight occupied line between the new disk and another dark disk, with one or more contiguous white disks
bounded
between them. During a move, all bounded disks of the opponent's color are turned over to the current's player color. A straight line involves: horizontal, vertical and diagonal lines in every possible direction.
It is possible to bound disks in more than one direction during a single move.
Players take turns to play. When a player doesn't have any valid moves, his turned is skipped. The game must keep going while there are valid moves by either player. The goal of the game is to have the
majority of the disks displaying your color
when there are no more possible moves.
We suggest that you play
an online version of the game
to grasp the idea.
Your Task
In this project, you will implement the rules and logic for Othello. You are provided with the skeleton code containing the
basic methods
that you need to complete to launch this game on the java console.
You have the freedom to use additional methods and variables to structure your solution, as long as the basic methods behave as expected.
Implementation Details
This project consists of just one class:
Othello
: it implements the logic of the game. You will implement the missing methods.
You should begin coding
after you have read the entire handout, understood the problem and made a plan for solving it.
Variables
The
Othello
clas ...
This document discusses adversarial search and game trees. It explains that adversarial search can model two-player zero-sum games where players take alternating turns maximizing or minimizing a score. Game trees represent the game as nodes for states and arcs for moves, branching into the future. The minimax algorithm recursively evaluates game trees from the leaves up, choosing the move leading to the highest score for the maximizing player and lowest for the minimizing player assuming optimal play. While effective for simple games, minimax is impractical for large games like chess without enhancements like alpha-beta pruning, evaluation functions, and depth limits.
The document provides information about game playing and constraint satisfaction problems (CSP). It discusses adversarial search techniques like minimax algorithm and alpha-beta pruning that are used for game playing. The minimax algorithm uses recursion to search through the game tree and find the optimal move. Alpha-beta pruning improves on minimax by pruning parts of the tree that are guaranteed not to affect the outcome. The document also mentions other topics like Monte Carlo tree search, stochastic games with elements of chance, and formalization of game state, actions, results, and utilities.
Techtude offers three versions of the ProTee Golf Simulator in South Africa: 1) a sensorpack kit to build your own simulator, 2) a full-size turnkey system for professionals, and 3) an indoor driving range version. The ProTee simulator uses advanced sensors and graphics to provide users with an immersive indoor golfing experience where they can play virtual rounds on multiple courses while analyzing their swing data. Techtude has experience installing simulators and identifies the ProTee as one of the most widely used and advanced professional systems available.
Intelligent Heuristics for the Game IsolationKory Becker
Learn how to create an artificial intelligence AI agent for the game, Isolation. We'll walk through how to create a web-based version of the game that can be played in the browser using React JavaScript. We'll also demonstrate how to create an artificial intelligence AI driven player by using the Minimax algorithm with Alpha-beta pruning and intelligent heuristics.
The document describes an Othello game and a C++ implementation of it. The Othello game is played on an 8x8 board with two players alternating turns to place disks, flipping the opponent's disks between the new disk and the player's other disks. The implemented version allows custom board sizes and uses data structures to represent the board as an array. It uses dynamic memory allocation, avoids globals, and pointers. Minimax algorithm is used to evaluate computer moves by assuming the opponent plays optimally.
The minmax algorithm is used in two-player turn-based games to determine the optimal move for a player assuming the opponent plays optimally. It works by having one player act as the maximizer trying to maximize their score, and the other as the minimizer trying to minimize the score. The algorithm analyzes all possible moves and countermoves to determine the outcome with the best score for the maximizer. It is optimal if both players play optimally but has limitations due to its exhaustive search of all possibilities.
Mobile devices, sensors, and GPSs are driving demand to handle big data in both batch and real time. This presentation discusses how we used complex event processing (CEP) and MapReduce-based technologies to track and process data from a soccer match as part of the annual DEBS event processing challenge. In 2013, the challenge included a data set generated by a real soccer match in which sensors were placed in the soccer ball and players’ shoes. This session will review how we used CEP to address the DEBS challenge and achieve throughput in excess of 100,000 events/sec. It will also examine how we extended the solution to conduct batch processing with business activity monitoring (BAM) using the same framework, enabling users to obtain both instant analytics as well as more detailed batch processing-based results.
AlphaGo Zero is an AI agent created by DeepMind to master the game of Go without human data or expertise. It uses reinforcement learning through self-play with the following key aspects:
1. It uses a single deep neural network that predicts both the next move and the winner of the game from the current board position. This dual network is trained solely through self-play reinforcement learning.
2. The neural network improves the Monte Carlo tree search used to select moves. The search uses the network predictions to guide selection and backup of information during search.
3. Training involves repeated self-play games to generate data, then using this data to update the neural network parameters through gradient descent. The updated network plays
The Mini-Max algorithm is a recursive algorithm used in game theory and decision making to find the optimal move for a player assuming the opponent also plays optimally. It works by having two players, MAX and MIN, where MAX aims to maximize their score and MIN aims to minimize MAX's score. The algorithm performs a depth-first search of the game tree, evaluating each terminal node and backing up values until it reaches the initial state node to determine the optimal first move.
Cryptocurrency Exchange Script like Binance.pptxriyageorge2024
This SlideShare dives into the process of developing a crypto exchange platform like Binance, one of the world’s largest and most successful cryptocurrency exchanges.
Microsoft AI Nonprofit Use Cases and Live Demo_2025.04.30.pdfTechSoup
In this webinar we will dive into the essentials of generative AI, address key AI concerns, and demonstrate how nonprofits can benefit from using Microsoft’s AI assistant, Copilot, to achieve their goals.
This event series to help nonprofits obtain Copilot skills is made possible by generous support from Microsoft.
What You’ll Learn in Part 2:
Explore real-world nonprofit use cases and success stories.
Participate in live demonstrations and a hands-on activity to see how you can use Microsoft 365 Copilot in your own work!
PRTG Network Monitor Crack Latest Version & Serial Key 2025 [100% Working]saimabibi60507
Copy & Past Link 👉👉
https://dr-up-community.info/
PRTG Network Monitor is a network monitoring software developed by Paessler that provides comprehensive monitoring of IT infrastructure, including servers, devices, applications, and network traffic. It helps identify bottlenecks, track performance, and troubleshoot issues across various network environments, both on-premises and in the cloud.
How can one start with crypto wallet development.pptxlaravinson24
This presentation is a beginner-friendly guide to developing a crypto wallet from scratch. It covers essential concepts such as wallet types, blockchain integration, key management, and security best practices. Ideal for developers and tech enthusiasts looking to enter the world of Web3 and decentralized finance.
Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev
If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic?
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AI based Tic Tac Toe game using Minimax Algorithm
1. Tic Tac Toe Genius
Artificial Intelligence (CU6051)
Submitted by: Submitted to:
Arjun Gurung (14046958) Mr. Sukant Kumar Sahu
Kiran Shahi (14046931) Module Leader
Date: 19th January, 2017
2. Aims And Objectives:
1. Introduction of the topic.
2. Current Scenario
3. System Functionality
4. Algorithm
5. Pseudocode
6. Future Enhancement
7. Reference
3. Introduction
Tic Tac Toe, very popular and easy to play.
Two players game.
3x3 grid most commonly used.
A paper and pen based game.
4. Why Tic Tac Toe
Rules for tic tac toe game is simple enough that we don't need an
elaborate analysis of game configurations.
Despite being a simple game, the basic AI principles shown here can be
applied to more complicated games such as checkers, Go and even
chess.
5. Present Scenario
• Many versions of tic tac toe like 3x3, 4x4 and even 9x9.
• Can be made on various platforms like Python, Java, C and even
JavaScript Canvas.
• Not so complex architecture.
6. Program Flow of Tic Tac Toe Genius
Start
Check
winning
point
Check
corner
space
Check
winning
move
for User
Check
Center
Check
diagona
l for (X)
Check
Side
Check
diagona
l for (0)
Take
move
Take move
Take move
Take move
Take move
Ask
User
to
take
move
System
wins
User
wins
Game is
draw
End
NO Yes
Yes
Yes
Yes
Yes
NO
NO
Yes
Yes
NO
NO
NO
NO
7. Functionality
• How to play Tic-Tac-Toe game?
• Some guiding steps to play the game are:
• The game is played between two players
• Both players choose their respective symbols to mark
• Player 1 starts the turn by placing his/her symbol on any of the nine squares
• Then player 2 marks the turn by placing his/her symbol on the empty squares
• Both players make their turns alternately
• If any player gets the three respective symbols in a horizontal, vertical or
diagonal row wins the game
8. Functionality
Winning Combinations in game:
In a tic-tac-toe game there are 8 possibilities to win the game. The
possibilities are getting the three combinations horizontally, three
combinations vertically or two combinations diagonally as shown in the
figure below. Hence, the easiest way to find the way to determine the
winner of the game is to check for these eight combinations as the
game goes on.
10. Game Strategies
• Win: If you have two in a row, play the third to get three in a row.
• Block: If the opponent has two in a row, play the third to block them.
• Fork: Create an opportunity where you can win in two ways.
• Block Opponent's Fork:
• Option 1: Create two in a row to force the opponent into defending, as long as it doesn't
result in them creating a fork or winning. For example, if "X" has a corner, "O" has the
centre, and "X" has the opposite corner as well, "O" must not play a corner in order to
win. (Playing a corner in this scenario creates a fork for "X" to win.)
• Option 2: If there is a configuration where the opponent can fork, block that fork.
• Centre: Play the centre.
• Opposite Corner: If the opponent is in the corner, play the opposite corner.
• Empty Corner: Play an empty corner.
• Empty Side: Play an empty side.
11. Algorithm Chosen
Mini-Max Algorithm
• Best suited for game with 2 player.
• To find a path from the starting position to a goal position.
• Calculate all possible game states by examining all opposing moves.
• Determine the next move against best play [opponent].
13. Algorithm
• Step 1: START
• Step 2: Check winning move for system (X). If there is such move, take it and
go to Step 7. Else go to Step 3.
• Step 3: Check wining move for user (O). It there is such move, then block the
player and go to Step 7. Else go to Step 4.
• Step 4: If there are corner spaces (i.e. 1, 3, 7, 9), take it and go to Step 7.
Else go to Step 5.
• Step 5: If there is center position, take it and go to step 7. Else go to Step 6.
• Step 6: If there are side positions (i.e. 2,4,6,8), take it and go to Step 7. Else
go to step 8. (Since there are no spaces left to move.)
• Step 7: Ask user to take a move and go to step 2.
14. Algorithm
• Step 8: Check system move (X) is in a vertical/horizontal/diagonal form.
If it is there the system will win. And go to step 11. Else go to step 9.
• Step 9: Check user’s move (O) is in a vertical/horizontal/diagonal form. If
it is there the system will lose. And go to step 11. Else go to step 10.
• Step 10: Game is draw and go to step 11:
• Step 11: END
15. Pseudocode
Find the path
CALL minimax
DO
GET available move
IF available move is
winning move
SET move to
available move
READ move
from User
ELSE IF available move is
winning move for User
SET move to
available move
READ move from
User
ELSE IF available move is
corner spaces
SET move to
available move
READ move from
User
ELSE IF available move is
centre space
SET move to available
move
READ move from User
ELSE IF available move is side
space
SET move to available
space
READ move from User
ELSE
CALL Check Result
END IF
END DO
16. Pseudocode
CheckScore
CALL checkScore
DO
IF System wins
Return 1
ElSE IF User wins
Return -1
ELSE
Return 0
END IF
END DO
CALL Check Result
DO
IF System move (X) is
diagonal
SET result win
CALL Check Score
ELSE IF User move (0) is
in diagonal
SET result lose
CALL Check Score
ELSE
SET result draw
CALL Check Score
END IF
END DO
17. Further Enhancement
• More number of winning strategies.
• Implementation of MINMAX algorithm into other games such as
checker, Go and even chess.
• Use of other Algorithms like Heuristic Search(BFS and DFS)
18. Conclusion
• An AI based game ‘Toc Tac Toe Genius’.
• Very popular and Entertaining.
• Not so complex use of Algorithm and Pseudocode.
• Number of possible winning combinations like horizontal, vertical and
Diagonal.
20. References
• Tic-tac-toe AI - Java Game Programming Case Study. 2017. Tic-tac-toe AI - Java Game
Programming Case Study. [ONLINE] Available at:
https://www.ntu.edu.sg/home/ehchua/programming/java/JavaGame_TicTacToe_AI.html. [Accessed
10 January 2017].
• Jason Fox. 2017. Tic Tac Toe: Understanding The Minimax Algorithm. [ONLINE] Available at:
http://neverstopbuilding.com/minimax. [Accessed 11 January 2017].
• How to use Minimax's algorithm to make a Tic-Tac-Toe - Quora. 2017. How to use Minimax's
algorithm to make a Tic-Tac-Toe - Quora. [ONLINE] Available at: https://www.quora.com/How-do-I-
use-Minimaxs-algorithm-to-make-a-Tic-Tac-Toe. [Accessed 10 January 2017].
• The Ludologist. 2017. 255,168 ways of playing Tic Tac Toe – The Ludologist. [ONLINE] Available at:
https://www.jesperjuul.net/ludologist/255168-ways-of-playing-tic-tac-toe. [Accessed 6 January
2017].