The LotR card game is difficult to compare to other fantasy and adventure card games, such as Magic the Gathering, Gwent or Hearthstone. "The objective of our paper was to implement an MCTS agent for the LotR game." "The 2016 Go tournament was the last moment when human players had a chance to compete with AI players," Sawicki and Godlewski explained.
These qualities make the game's rules and strategies very difficult to acquire by computational methods. In fact, LotR is a cooperative card game characterized by a huge space of possible solutions, a complex logical structure and the possibility of random events occurring. The main reason why a computational method that can play the LotR card game did not yet exist is that developing such a method is highly challenging. "Nonetheless, we found applications of tree search methods for similar card games such as Magic: The Gathering or Hearthstone." "We are fans of the card game LotR, but we found that there were no existing AI approaches that could play this game," Bartosz Sawicki and Konrad Godlewski, the two researchers who carried out the study, told TechXplore. The researchers presented their MCTS technique in a recent paper pre-published on arXiv. An MCTS algorithm is a universal heuristic decision method that can optimize the searching solution space in a given game or scenario, by playing a series of random games, known as 'playouts'. Researchers at Warsaw University of Technology have recently set out to develop a technique based on Monte Carlo tree search (MCTS) algorithms that could play the Lord of the Rings (LotR) classic card game, released in 2011 by Fantasy Flight Games. Some of these artificial agents have achieved remarkable results, beating established human champions and game experts. Over the past decade or so, developers have trained numerous other models to play against humans at strategy games, board games, computer games and card games.
0 kommentar(er)
