使用强化学习的游戏AI

Amogh Sawant, Shahid Shaikh, Dharmesh Sharma
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摘要

人工智能(AI)是通往未来的道路。目前,许多企业是由人工智能而不是人类监管的;尽管如此,许多目前由人类监督的任务可以更好地利用人工智能来完成。然而,由于人工智能的创新还不是最先进的,所以现在是不可想象的。因此,我们希望培养一个通过电脑游戏准备的人工智能,并让它掌握复杂而实用的能力。这是可以想象的,因为玩电脑游戏所需要的智力和它们动态而复杂的环境。电子游戏特别有价值,因为我们可以通过对比不同玩家的得分来迅速调查专家的表现。我们可以把电子游戏想象成人类能力的缩影,因为它们在人类文化中如此多样化和普遍。通过这种方式,它们对于评估和展示人工智能非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Game AI using Reinforcement Learning
Artificial Intelligence (AI) is the way into the future. Many undertakings are currently overseen by an AI rather than a human; nonetheless, many tasks that are as yet overseen by people can be better done utilizing an AI. However, since the AI innovation isn’t cutting edge as yet, it is unimaginable for now. Thus, we desire to foster an AI prepared through computer games, and for it to master intricate and pragmatic abilities playing them. This is conceivable through the intellectual abilities needed to play computer games and their dynamic and tangled climate. Video games are exceptionally valuable since we can promptly investigate how the specialist performs by contrasting its score with different players. We can imagine video games as a microcosm of human capacity since they are so various and pervasive across human culture. In this way, they are extraordinarily significant to evaluate and demonstrate AI.
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