论文标题

TotalBotwar:新的伪实时多进攻游戏挑战和AI的竞争

TotalBotWar: A New Pseudo Real-time Multi-action Game Challenge and Competition for AI

论文作者

Estaben, Alejandro, Díaz, César, Montoliu, Raul, Pérez-Liebana, Diego

论文摘要

本文介绍了TotalBotwar,这是针对游戏AI的新伪实时多进攻挑战,以及一些初始实验,可以用不同的代理进行基于框架进行基准测试。该游戏基于流行的全球游戏系列的实时战斗,玩家管理一支军队以击败对手的比赛。在拟议的游戏中,转弯由一组控制单元的订单组成。在游戏的进展过程中,可以在转弯中执行的数量和特定订单各不相同。游戏的一个有趣功能是,如果特定单元在回合中未收到订单,它将继续执行上一回合中指定的操作。对于传统算法而言,转弯的分支因素变得压倒性,并且游戏状态的部分可观察性使拟议的游戏成为测试现代AI算法的有趣平台。

This paper presents TotalBotWar, a new pseudo real-time multi-action challenge for game AI, as well as some initial experiments that benchmark the framework with different agents. The game is based on the real-time battles of the popular TotalWar games series where players manage an army to defeat the opponent's one. In the proposed game, a turn consists of a set of orders to control the units. The number and specific orders that can be performed in a turn vary during the progression of the game. One interesting feature of the game is that if a particular unit does not receive an order in a turn, it will continue performing the action specified in a previous turn. The turn-wise branching factor becomes overwhelming for traditional algorithms and the partial observability of the game state makes the proposed game an interesting platform to test modern AI algorithms.

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