陈锶奇
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主要研究方向：人工智能、多agent系统、管理科学、生物信息计算
近3年论文：
MFA-DTI : Drug-target interaction prediction based on multi-feature fusion adopted framework. Methods. 2024. (IF=4.8)
PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants. Plant Physiology. 2024.(IF=7.4)
ANOTO: Improving Automated Negotiation via Offline-to-Online Reinforcement Learning. AAMAS 2024(CCF-B会议).
An effective negotiating agent framework based on deep offline reinforcement learning. UAI 2023 (CCF-B会议).
Transfer Learning based Agent for Automated Negotiation. AAMAS 2023(CCF-B会议).
DNN-PNN: A parallel deep neural network model to improve anticancer drug sensitivity. Methods. 2023. (IF=4.8)
Transfer Reinforcement Learning Based Negotiating Agent Framework. PAKDD 2023 (CCF-C会议).
A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data.PLoS Computational Biology. 2022. (IF=4.3)
An autonomous agent for negotiation with multiple communication channels using parametrized deep q-network. Mathematical Biosciences and Engineering. 2022. (IF=2.6)
An Intelligent Chatbot for Negotiation Dialogues. UIC 2022 (CCF-C会议).
Detecting and Learning Against Unknown Opponents for Automated Negotiations. PRICAI 2021(CCF-C会议，Best paper runner-up award)
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