His scientific interests lie mostly in Computer security, Stackelberg competition, Game theory, Patrolling and Adversary. His work deals with themes such as Risk analysis and Resource allocation, which intersect with Computer security. The Resource allocation study combines topics in areas such as Supply and demand, Computer security model and Combinatorial auction.
As part of one scientific family, Bo An deals mainly with the area of Stackelberg competition, narrowing it down to issues related to the Expected utility hypothesis, and often Exploit, Critical infrastructure protection and Optimal stopping. His Game theory research includes themes of Automotive engineering and Mathematical optimization. In the subject of general Mathematical optimization, his work in Bilevel optimization is often linked to Traffic congestion, thereby combining diverse domains of study.
His primary areas of study are Mathematical optimization, Artificial intelligence, Game theory, Computer security and Stackelberg competition. His Mathematical optimization study frequently draws connections to other fields, such as Time complexity. His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Transitive relation.
His Game theory study also includes
Bo An mainly investigates Artificial intelligence, Reinforcement learning, Mathematical optimization, Machine learning and Benchmark. His work in the fields of Artificial intelligence, such as Deep learning and Regularization, overlaps with other areas such as Positive feedback, Expectation–maximization algorithm and Learning environment. His research in Reinforcement learning intersects with topics in Web page, Portfolio, Solution concept and Operations research.
His Mathematical optimization study combines topics in areas such as Expected shortfall, CVAR and Extensive-form game. Game theory is closely connected to Heuristic in his research, which is encompassed under the umbrella topic of Algorithm. The concepts of his Game theory study are interwoven with issues in Linear programming and Generator.
Artificial intelligence, Deep learning, Reinforcement learning, Set and Consistency are his primary areas of study. Particularly relevant to Gradient descent is his body of work in Artificial intelligence. His Deep learning study is concerned with the larger field of Machine learning.
His Reinforcement learning research integrates issues from Correlated equilibrium, Scheduling, Bandwidth and Operations research. As a part of the same scientific study, he usually deals with the Data mining, concentrating on Benchmark and frequently concerns with Reliability, Social network, Crowdsourcing and Set. His studies in Human–computer interaction integrate themes in fields like Game theory, Solution concept, Recommender system, Web page and Ranking.
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PROTECT: a deployed game theoretic system to protect the ports of the United States
Eric Shieh;Bo An;Rong Yang;Milind Tambe.
Automated negotiation with decommitment for dynamic resource allocation in cloud computing
Bo An;Victor Lesser;David Irwin;Michael Zink.
Optimal Electric Vehicle Fast Charging Station Placement Based on Game Theoretical Framework
Yanhai Xiong;Jiarui Gan;Bo An;Chunyan Miao.
IEEE Transactions on Intelligent Transportation Systems (2018)
POI2Vec: Geographical Latent Representation for Predicting Future Visitors
Shanshan Feng;Gao Cong;Bo An;Yeow Meng Chee.
national conference on artificial intelligence (2017)
Deploying PAWS: field optimization of the protection assistant for wildlife security
Fei Fang;Thanh H. Nguyen;Rob Pickles;Wai Y. Lam.
Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization
Hongxin Wei;Lei Feng;Xiangyu Chen;Bo An.
computer vision and pattern recognition (2020)
GUARDS and PROTECT: next generation applications of security games
Bo An;James Pita;Eric Shieh;Milind Tambe.
Stackelberg security games: Looking beyond a decade of success
Arunesh Sinha;Fei Fang;Bo An;Christopher Kiekintveld.
Strategic agents for multi-resource negotiation
Bo An;Victor Lesser;Kwang Mong Sim.
Challenges and Opportunities for Trust Management in Crowdsourcing
Han Yu;Zhiqi Shen;Chunyan Miao;Bo An.
web intelligence (2012)
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