11 machine learning datasets
11 dataset results
V-D4RL provides pixel-based analogues of the popular D4RL benchmarking tasks, derived from the dm_control suite, along with natural extensions of two state-of-the-art online pixel-based continuous control algorithms, DrQ-v2 and DreamerV2, to the offline setting.
7,672 human written natural language navigation instructions for routes in OpenStreetMap with a focus on visual landmarks. Validated in Street View.
The eSports Sensors dataset contains sensor data collected from 10 players in 22 matches in League of Legends. The sensor data collected includes:
Replay data from human players and AI agents navigating in a 3D game environment.
StarData is a StarCraft: Brood War replay dataset, with 65,646 games. The full dataset after compression is 365 GB, 1535 million frames, and 496 million player actions. The entire frame data was dumped out at 8 frames per second.
RL Unplugged is suite of benchmarks for offline reinforcement learning. The RL Unplugged is designed around the following considerations: to facilitate ease of use, we provide the datasets with a unified API which makes it easy for the practitioner to work with all data in the suite once a general pipeline has been established. This is a dataset accompanying the paper RL Unplugged: Benchmarks for Offline Reinforcement Learning.
Raw StarCraft II data is subject to processing under the Blizzard end user license agreement (EULA), and in special cases Blizzard AI and Machine Learning License may be applied. Please refer to the materials listed below.
SC2EGSet: StarCraft II Esport Game State Dataset
In this dataset, we provide detailed traffic stream data for the Spot robot, including both the Spot robot control traffic stream and the Spot video stream. The Spot robot traffic streams provide realistic traffic data for communication network evaluations, e.g., for measurements with the TSN FlexText testbed. Furthermore, we share data for the tactile internet including audio, video, and robotic communication. Finally, the dataset includes generic data streams for three different intervals (0.2ms, 0.3ms, and 0.5ms) with two different Ethernet frame sizes. The data is provided as .*pcap which can be replayed with various tools or be analyzed, e.g., with Wireshark. The Spot data streams are split into two directions and are based on Spot API calls.
Whole-body, low-level control/manipulation demonstration dataset for ManiSkill-HAB. Demonstrations are organized by task-subtask-object. All demos use RGBD (128x128) and state. JSON files store metadata (tincluding even labels and success/failure mode), while HDF5 files store demonstration data.
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