将强化学习应用于迭代囚徒困境（IPD）游戏，我们的项目开发了人工智能代理，以通过重复交互学习最优策略。我们探索各种玩家策略并评估其绩效，为战略决策动态和人工智能驱动的合作行为提供见解。
Applying reinforcement learning to the Iterated Prisoner s Dilemma (IPD) game, our project develops AI agents to learn optimal strategies through repeated interactions. We explore various player strategies and evaluate their performance, offering insights into strategic decision-making dynamics and AI-driven cooperative behavior. (2024-04-30, Python, 0KB, 下载0次)
人民选择信用合作社api的逆向工程，
Reverse engineering of the peoples choice credit union api, (2018-05-28, Python, 0KB, 下载0次)
一种双向双信任感知推荐系统，该系统结合了源的可信度和用户关系，以提供...，
A bi-directional dual trust-aware recommender system that incorporates trustworthiness of source and users’ relationships to provide the reliable, trustworthy resources as a whole to end-users for the better decision-making process (2021-07-08, Python, 0KB, 下载0次)
Telkom大学使用模糊逻辑作为人工智能任务的奖学金决策，
Scholarship decision-making using Fuzzy Logic as Artificial Intelligence task at Telkom University, (2021-03-18, Python, 0KB, 下载0次)
用于临床辅助决策的合作双医学本体表示学习的源代码，
The source code for Cooperative Dual Medical Ontology Representation Learning for Clinical Assisted Decision-Making, (2023-06-15, Python, 0KB, 下载0次)
本文的源代码：图强化学习在混合自主交通中合作决策中的应用：框架...，
The source code for our paper: Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges. This code is developed based on our previous repository TorchGRL. (2022-11-17, Python, 0KB, 下载0次)