Agents
Bandit Task Assignment with Unknown Processing Time
These regret bounds nearly match lower bounds.
4a5876b450b45371f6cfe5047ac8cd45-Supplemental.pdf
In the following equation, we use the results inAppendix D.1 tocalculate the probability that there exists some arm whose mean value isaboveitsconfidence intervalofwidth
4a5876b450b45371f6cfe5047ac8cd45-Paper.pdf
The goal is to find the global optimal arm, and agents are able to pull any arm; however, they can only observe the reward when the selected arm is local.
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning Hao Bai 1,2 Yifei Zhou
While training with static demonstrations has shown some promise, we show that such methods fall short for controlling real GUIs due to their failure to deal with real world stochasticity and non-stationarity not captured in static observational data.
LanguageandVisualEntityRelationshipGraph forAgentNavigation
Vision-and-language navigation in the real-world is an important step towards building mobile agents that perceivetheir environments and complete specific tasks following human instructions.
Efficient Subgame Refinement for Extensive-form Games
However, directly applying existing subgame solving techniques may be difficult, due to the intricate nature and substantial size of many real-world games.
