Dataset Groups Activity Stream R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games The dataset used in the paper is a synthetic game with two agents, where the payoff functions are sampled from a Gaussian process. BibTex: @dataset{Zhongxiang_Dai_and_Yizhou_Chen_and_Bryan_Kian_Hsiang_Low_and_Patrick_Jaillet_and_Teck-Hua_Ho_2024, abstract = {The dataset used in the paper is a synthetic game with two agents, where the payoff functions are sampled from a Gaussian process.}, author = {Zhongxiang Dai and Yizhou Chen and Bryan Kian Hsiang Low and Patrick Jaillet and Teck-Hua Ho}, doi = {10.57702/4ud3ul0w}, institution = {No Organization}, keyword = {'Bayesian Optimization', 'Gaussian Process', 'No-Regret Learning'}, month = {dec}, publisher = {TIB}, title = {R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games}, url = {https://service.tib.eu/ldmservice/dataset/r2-b2--recursive-reasoning-based-bayesian-optimization-for-no-regret-learning-in-games}, year = {2024} }
