game-theory | generating payoff matrix | Math library

 by   Sepante Python Version: Current License: GPL-3.0

kandi X-RAY | game-theory Summary

kandi X-RAY | game-theory Summary

game-theory is a Python library typically used in Utilities, Math applications. game-theory has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However game-theory build file is not available. You can download it from GitHub.

generating payoff matrix (temp)
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            kandi-support Support

              game-theory has a low active ecosystem.
              It has 1 star(s) with 0 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              game-theory has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of game-theory is current.

            kandi-Quality Quality

              game-theory has 0 bugs and 0 code smells.

            kandi-Security Security

              game-theory has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              game-theory code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              game-theory is licensed under the GPL-3.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              game-theory releases are not available. You will need to build from source code and install.
              game-theory has no build file. You will be need to create the build yourself to build the component from source.
              It has 37 lines of code, 1 functions and 1 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed game-theory and discovered the below as its top functions. This is intended to give you an instant insight into game-theory implemented functionality, and help decide if they suit your requirements.
            • Calculates the reward .
            Get all kandi verified functions for this library.

            game-theory Key Features

            No Key Features are available at this moment for game-theory.

            game-theory Examples and Code Snippets

            No Code Snippets are available at this moment for game-theory.

            Community Discussions

            QUESTION

            Cannot get minimax function to work for tic tac toe game
            Asked 2021-Apr-08 at 01:07
            const grabEmptySquares = (array) => {
              var emptyGameSquares = [];
              for (i = 0; i < 9; i++) {
                if (!array[i]) emptyGameSquares.push(i);
              }
              return emptyGameSquares;
            };
            
            function findBestMove(board) {
              var bestMove = {
                index: null,
                evaluation: null,
              };
              var availableMoves = grabEmptySquares(board);
              availableMoves.forEach((move) => {
                const simulGameboard = JSON.parse(JSON.stringify(board));
                simulGameboard[move] = "o";
                const evaluation = minimax(simulGameboard, 1, false);
                const moveDetails = {
                  index: move,
                  evaluation: evaluation,
                };
                console.log(moveDetails)
            
                if (evaluation > bestMove.evaluation || bestMove.evaluation === null) {
                  bestMove.index = move;
                  bestMove.evaluation = evaluation;
                }
              });
            
              return bestMove.index;
            }
            
            function evaluate(board, isMaximizingPlayer, depth) {
              var gameStatus = isGameOver(board);
              if (gameStatus[0] != true) return;
              if (gameStatus[1] === "win")
                return isMaximizingPlayer ? +10 - depth : -10 + depth;
              if (gameStatus[1] === "tie") return 0;
            }
            
            function minimax(board, depth, isMaximizingPlayer) {
              var gameStatus = isGameOver(board);
              if (gameStatus[0] == true) {
                const evaluation = evaluate(board, !isMaximizingPlayer, depth);
                return evaluation;
              }
            
              var simulGameboard = JSON.parse(JSON.stringify(board));
              var availableMoves = grabEmptySquares(simulGameboard);
            
              if (isMaximizingPlayer) {
                bestVal = -Infinity;
                availableMoves.forEach((move) => {
                  depth % 2 === 0
                    ? (simulGameboard[move] = "o")
                    : (simulGameboard[move] = "x");
                  value = minimax(simulGameboard, depth + 1, false);
                  bestVal = Math.max(bestVal, value);
            
                  const moveDetails = {
                    index: move,
                    evaluation: bestVal,
                    depth: depth,
                  };
                  console.log(moveDetails);
                });
                return bestVal;
              } else {
                bestVal = Infinity;
                availableMoves.forEach((move) => {
                  depth % 2 === 0
                    ? (simulGameboard[move] = "o")
                    : (simulGameboard[move] = "x");
            
                  value = minimax(simulGameboard, depth + 1, true);
                  bestVal = Math.min(bestVal, value);
            
                  const moveDetails = {
                    index: move,
                    evaluation: bestVal,
                    depth: depth,
                  };
                  console.log(moveDetails);
                });
                return bestVal;
              }
            }
            
            function isGameOver(array) {
              var gameOver = false;
              if (
                (array[0] && array[0] === array[1] && array[0] === array[2]) ||
                (array[3] && array[3] === array[4] && array[3] === array[5]) ||
                (array[6] && array[6] === array[7] && array[6] === array[8])
              ) {
                return (gameOver = [true, "win"]);
              }
              if (
                (array[0] && array[0] === array[4] && array[0] === array[8]) ||
                (array[2] && array[2] === array[4] && array[2] === array[6])
              ) {
                return (gameOver = [true, "win"]);
              }
              if (
                (array[1] && array[1] === array[4] && array[4] === array[7]) ||
                (array[0] && array[0] === array[3] && array[3] === array[6]) ||
                (array[2] && array[2] === array[5] && array[5] === array[8])
              ) {
                return (gameOver = [true, "win"]);
              }
              if ([...array].every((index) => index)) {
                return (gameOver = [true, "tie"]);
              }
              return (gameOver = [false, null]);
            }
            
            ...

            ANSWER

            Answered 2021-Apr-08 at 01:07

            This isn't the easist code to read, but AFAICT the minimax function copies the game board state once and then loops through possible moves with availableMoves.forEach. This means that when evaluating each possible move, it acts as if each previously considered move had been made. Move the copy inside the forEach and things should make somewhat more sense.

            You already have this in the findBestMove function. I'd strongly suggest unifying findBestMove and minimax (and the sides of the isMaximizingPlayer branch inside minimax). Having very similar code in multiple places makes it hard to remember where you have and haven't fixed things.

            I'd also suggest replacing the isMaximizingPlayer and depth%2 logic with a player variable that can be either "x" or "o", and multiplying goodness scores by -1 as needed. It'll be easier to keep track of.

            Source https://stackoverflow.com/questions/66977730

            QUESTION

            Guaranteeing values in types in haskell
            Asked 2020-Oct-20 at 08:37

            I have a data type called Interaction which is as follows:

            ...

            ANSWER

            Answered 2020-Oct-20 at 01:17

            The problem here is that Maybe Action is the correct answer to the question "what is the action in the Interaction associated with the AgentID who isn't me?" If you want the answer type to be Action you will have to ask a different question, or you will have to change the Interaction type. The only way to ensure that the answer will be an Action is to guarantee that one of a and b won't equal me. So lets create a type that can't express "a and b both of whom are me", that is, "me and b | a and me | two who aren't me":

            Source https://stackoverflow.com/questions/64436147

            QUESTION

            TicTacToeAI with Minimax Algorithm
            Asked 2020-Sep-15 at 13:23

            I have implemented Minimax Algorithm for Tic Tac Toe Game from GeeksForGeeks. I know how the Minimax Algorithm works but my code here doesn't work according to it. I have checked and checked for the things I might be doing wrong and also have debugged it. But it seems, I am not able to find it.

            Please look into the algorithm, it would be much thankful for extra set of eyes and to find the incorrect part which I can't seem to find.

            I have commented every part of the code that is helpful with Minimax Algorithm. I think it would be easy to catch up.

            Please help me out here.

            Thank you.

            ...

            ANSWER

            Answered 2020-Sep-15 at 13:23

            There a mismatch between your function checkForSpace() and its use in minimax(). If there is space left you return false and if you get a false in minimax() you stop the search as if there is a tie. You need to invert the boolean in checkForSpace() or remove the logical not in minimax().

            You should propably rename checkForSpace() and other function that return a boolean. From The Art of Readable Code (Dustin Boswell and Trevor Foucher):

            When picking a name for a boolean variable or a function that returns a boolean, be sure it’s clear what true and false really mean.

            Here’s a dangerous example:

            Source https://stackoverflow.com/questions/63335279

            QUESTION

            unbeatable Tic Tac Toe
            Asked 2020-Aug-24 at 13:11

            i'm trying to make a unbeatable tic tac toe for a side project and i can't make it right (i can actually beat it ironically). It's actually a implementation of the MiniMax algorithm; i came with this code

            ...

            ANSWER

            Answered 2020-Aug-24 at 13:11

            There are multiple bugs in your code:

            • You are checking the value of grid[0][0] in grid[0][2] == grid[1][1] && grid[0][2] == grid[2][0] case of the function evaluateBoard. It should be grid[0][2].
            • playerMov(grid); in the function playerMov should be return playerMov(grid);. Otherwise, the re-entered "correct" values will be dropped and (partly) uninitalized playerMov will be returned.
            • You should update best to moveValue when moveValue > best in the function findMove. (this should be the cause of the issue on your question)

            Source https://stackoverflow.com/questions/63561634

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install game-theory

            You can download it from GitHub.
            You can use game-theory like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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