DUNGEON BATTLE ARENA: TURN-BASED PERFECT INFORMATION STRATEGY BOARD GAME WITH ARTIFICIAL INTELLIGENCE USING MINIMAXALGORITHM WITH ALPHA BETA PRUNINGOPTIMIZATION TECHNIQUE

Abstract

Entertainment comes from various forms and activities, one of which is by playing games. Most of them are currently being played on electronic devices such as smartphones, tablets, laptops, and personal computer. There are two kinds of strategy game including perfect information game where both players have all of the information about the game when making any decision and imperfect information game where they do not have all of the information at that point. Board games are usually played by 2 or more people. But with the development of Artificial Intelligence, the modern board games can be played alone with AI controlling the other players. One of the algorithms that can be used to develop the AI is minimax algorithm. Minimax algorithm is a decision- making algorithm that works by minimizing the losing possibilities on a worst- case scenario. This algorithm will cover all of player moves possibilities and decide the best move based on the value of the move. To improve the algorithm performance, alpha-beta pruning optimization technique could work by pruning some of the decisions when there are better options that are already explored. This final project, Dungeon Battle Arena will combine the perfect information strategy board game with AI using minimax algorithm and alpha- beta pruning optimization technique by turn it into a 2D computer game with all of the important elements attached. The player(s) will select a character that they will control in the game based on a turn system. Each character has their own unique skills and status. The goal of the game is to reduce the enemy health bar to zero with a twist where the arena itself is destructible thus the health bar of any character will instantly be depleted when it is on a destroyed portion of the arena.