adversarial environment

Caution for the Environment: Multimodal LLM Agents are Susceptible to Environmental Distractions ACL 2025 High-Dimensional Prediction for Sequential Decision Making ICML 2025 Non-stochastic Bandits With Evolving Observations ALT 2025 Adversarial Environment Design via Regret-Guided Diffusion Models NeurIPS 2024 Online Composite Optimization Between Stochastic and Adversarial Environments NeurIPS 2024 Online Policy Optimization for Robust Markov Decision Process UAI 2024 An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits NeurIPS 2023 Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds COLT 2023 Online Nonstochastic Model-Free Reinforcement Learning NeurIPS 2023 EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning ICML 2022 Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs NeurIPS 2022 RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning NeurIPS 2022 Parameter-Free Multi-Armed Bandit Algorithms with Hybrid Data-Dependent Regret Bounds COLT 2021 Adaptive Aggregation of Arbitrary Online Trackers with a Regret Bound WACV 2020 Multi-Player Bandits: The Adversarial Case JMLR 2020 Synthesizing strategies under expected and exceptional environment behaviors IJCAI 2020 Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously ICML 2019 Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments AISTATS 2018 Robotic Strategic Behavior in Adversarial Environments IJCAI 2017