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game interactive learning:A New Paradigm towards Intelligent Decision-Making

CAAI Artificial Intelligence Research 2023年第1期2卷 65-74页

作者： Junliang Xing Zhe Wu Zhaoke Yu Renye Yan Zhipeng Ji Pin Tao Yuanchun Shi Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Qiyuan Laboratory Beijing 100094China

Decision-making plays an essential role in various real-world systems like automatic driving,traffic dispatching,information system management,and emergency command and *** breakthroughs in computer game scenarios using deep reinforcement learning for intelligent decision-making have paved decision-making intelligence as a burgeoning research *** complex practical systems,however,factors like coupled distracting features,long-term interact links,and adversarial environments and opponents,make decision-making in practical applications challenging in modeling,computing,and *** work proposes game interactive learning,a novel paradigm as a new approach towards intelligent decision-making in complex and adversarial *** novel paradigm highlights the function and role of a human in the process of intelligent decision-making in complex *** formalizes a new learning paradigm for exchanging information and knowledge between humans and the machine *** proposed paradigm first inherits methods in game theory to model the agents and their preferences in the complex decision-making *** then optimizes the learning objectives from equilibrium analysis using reformed machine learning algorithms to compute and pursue promising decision results for *** interactions are involved when the learning process needs guidance from additional knowledge and instructions,or the human wants to understand the learning machine *** perform preliminary experimental verification of the proposed paradigm on two challenging decision-making tasks in tactical-level War-game *** results demonstrate the effectiveness of the proposed learning paradigm.

关键词： decision-making game interactive learning human-computer interaction game theory machine learning

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