Agents
Iteratively Learn Diverse Strategies with State Distance Information
In addition, we examine two common computation frameworks for this problem, i.e., population-based training (PBT) and iterative learning
Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks Y un Qu
We also introduce a novel baseline algorithm tailored for the inherent hierarchical action space of the game.
Calibrating " Cheap Signals " in Peer Review without a Prior
Detecting and correcting bias is challenging, as ratings are subjective and unverifiable. Unlike previous works relying on prior knowledge or historical data, we propose a one-shot noise calibration process without any prior information.
Alexa Arena: A User-Centric Interactive Platform for Embodied AI
Alexa Arena features multi-room layouts and an abundance of interactable objects.
Safety-Gymnasium: A Unified Safe Reinforcement Learning Benchmark
Artificial intelligence (AI) systems possess significant potential to drive societal progress. However, their deployment often faces obstacles due to substantial safety concerns.
Safety-Gymnasium: A Unified Safe Reinforcement Learning Benchmark
Artificial intelligence (AI) systems possess significant potential to drive societal progress. However, their deployment often faces obstacles due to substantial safety concerns.