scholarly journals Enhancements for real-time Monte-Carlo Tree Search in General Video Game Playing

2016 ◽  
Author(s):  
Dennis J. N. J. Soemers ◽  
Chiara F. Sironi ◽  
Torsten Schuster ◽  
Mark H. M. Winands
Keyword(s):  
Monte Carlo ◽  
Real Time ◽  
Video Game ◽  
Tree Search ◽  
Game Playing ◽  
Monte Carlo Tree Search ◽  
Video Game Playing

Game State and Action Abstracting Monte Carlo Tree Search for General Strategy Game-Playing

2021 ◽  
Author(s):  
Alexander Dockhorn ◽  
Jorge Hurtado-Grueso ◽  
Dominik Jeurissen ◽  
Linjie Xu ◽  
Diego Perez-Liebana
Keyword(s):  
Monte Carlo ◽  
General Strategy ◽  
Tree Search ◽  
Game Playing ◽  
Monte Carlo Tree Search ◽  
Strategy Game ◽  
Game State

scholarly journals Real-Time Monte Carlo Tree Search in Ms Pac-Man

2014 ◽  
Vol 6 (3) ◽  
pp. 245-257 ◽  
Author(s):  
Tom Pepels ◽  
Mark H. M. Winands ◽  
Marc Lanctot
Keyword(s):  
Monte Carlo ◽  
Real Time ◽  
Tree Search ◽  
Monte Carlo Tree Search

Monte Carlo Tree Search and Cognitive Hierarchy Theory for Interactive-Behavior Prediction in Fast Trajectory Planning and Automated Lane Change

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Shahab Karimi ◽  
Ardalan Vahidi
Keyword(s):  
Monte Carlo ◽  
Real Time ◽  
Trajectory Planning ◽  
Hierarchy Theory ◽  
Lane Change ◽  
Tree Search ◽  
Behavior Prediction ◽  
Highway Traffic ◽  
Monte Carlo Tree Search ◽  
Cognitive Hierarchy

Abstract Predicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communications and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. The main goal of this paper is to develop a fast algorithm that predicts the future states of the neighboring vehicles. The proposed workflow employs Monte Carlo Tree Search (MCTS) along with an on-policy learning technique for fast trajectory planning in multi-lane highway traffic scenarios. Also, for the inclusion of behavioral aspects, cognitive hierarchy and level-K game theories are utilized to predict the reaction and decision of the surrounding drivers. Simulation case studies demonstrate that our proposed approach is real-time implementable and can often avoid collision in difficult simulated confrontations.

Sign in / Sign up

Export Citation Format

Share Document