Essays about: "MCTS Tree Search Simulation"

Found 5 essays containing the words MCTS Tree Search Simulation.

  1. 1. Monte-Carlo Tree Search for Fox Game

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Anton Janshagen; Olof Mattsson; [2022]
    Keywords : Monte-Carlo Tree Search; Artificial Intelligence; Fox Game; Cutoff; Heuristic Function;

    Abstract : This report explores if Monte-Carlo Tree Search (MCTS) can perform well in Fox Game, a classic Scandinavian strategy game. MCTS is implemented using a cutoff in the simulation phase. The game state is then evaluated using a heuristic function that is formulated using theoretical arguments from its chess counterpart. READ MORE

  3. 2. Monte-Carlo Tree Search in Continuous Action Spaces for Autonomous Racing : F1-tenth

    University essay from Högskolan i Halmstad/Akademin för informationsteknologi

    Author : Jonatan Jönsson; Felix Stenbäck; [2020]
    Keywords : mcts monte-carlo tree search ai machine learning regression neural network autonoumous vehicle f1tenth computer science master;

    Abstract : Autonomous cars involve problems with control and planning. In thispaper, we implement and evaluate an autonomous agent based ona Monte-Carlo Tree Search in continuous action space. To facilitatethe algorithm, we extend an existing simulation framework and usea GPU for faster calculations. READ MORE

  4. 3. Simulating Human Game Play for Level Difficulty Estimation with Convolutional Neural Networks

    University essay from KTH/Skolan för informations- och kommunikationsteknik (ICT)

    Author : Philipp Eisen; [2017]
    Keywords : ;

    Abstract : This thesis presents an approach to predict the difficulty of levels in a game by simulating game play following a policy learned from human game play. Using state-action pairs tracked from players of the game Candy Crush Saga, we train a Convolutional Neural Network to predict an action given a game state. The trained model then acts as a policy. READ MORE

  5. 4. Crushing Candy Crush : Predicting Human Success Rate in a Mobile Game using Monte-Carlo Tree Search

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : Erik Ragnar Poromaa; [2017]
    Keywords : MCTS Tree Search Simulation;

    Abstract : The purpose of this thesis is to evaluate the possibility of predicting difficulty, measured in average human success rate (AHSR), across game levels of a mobile game using a general AI algorithm. We implemented and tested a simulation based bot using MCTS for Candy. READ MORE

  6. 5. Go Go! - Evaluating Different Variants of Monte Carlo Tree Search for Playing Go

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : Carl Frendin; Andreas Sjöroos; [2014]
    Keywords : ;

    Abstract : Monte Carlo Tree Search (MCTS) is a Go algorithm that is used in many recent strong go playing agents. In this report we test and compare different algorithms related to Monte Carlo simulation, seeing how well they do against each other under different time constraints on consumer hardware. READ MORE