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Offline RL trajectories, game data, robot demonstrations, RLHF, multi-agent interaction
10,022 datasets
Active formal appointments between individual agents or adjusters and regulated insurance companies, as recorded by the City of Austin. The dataset distinguishes appointments from business relationships and agency appointments, which are covered in separate datasets. It was last updated in March 2026.
Campaign finance data from the City of Austin details reports filed by political committees. It includes information on report types, due dates, original filing dates, and transaction totals. This dataset links to a separate transaction detail table for individual contributions and expenditures.
City of Austin provides a dataset of formal appointments between insurance agencies and regulated insurance companies. The data is structured in tabular format and available in JSON, CSV, XML, and RDF file formats. It was last updated in March 2026.
OS Emergency Services Gazetteer provides a national, consistent, and maintained view of locations and names of places and objects. The dataset is produced by the Government Digital Service and aggregated from the eu_open_data platform. It is intended to support Protection of Life use cases.
Order transaction records from an e-commerce platform, sourced from Kaggle. The dataset's specific size, time range, and features are not detailed in the provided metadata. Its content and structure require verification after download.
Laboratory experiments and survey data investigate why low-income individuals may oppose redistribution. The data likely contains results from risk-choice games and money-transfer games, as well as survey responses on minimum-wage attitudes. Author Ilyana Kuziemko and colleagues produced this research dataset.
Experimental data from three studies investigating how perceptual fluency influences cue weighting in judgment, independent of objective cue validity. The data was generated by Anuj Shah of Princeton University. The dataset's size, specific row count, and last update date are unknown.
A paper by James Garbarino of The Family Center analyzing violent behavior in children from a psychosocial perspective. The work provides six basic tools for understanding and addressing youth violence, considering factors like ecological development, risk accumulation, and child temperament. The abstract describes the evolution of children's expressions of frustration from vandalism to weapon use.
2,000 high school students are represented in this dataset focused on burnout prediction. The data includes information on daily schedules and perceived support. It was sourced from Kaggle, but the original author, collection method, and specific time period are not detailed.
Checkpoint files for a reinforcement learning agent trained on a Bomberman game environment using the Proximal Policy Optimization (PPO) algorithm. The dataset is hosted on Kaggle and includes platform tags for Game AI and Reinforcement Learning. The specific contents, such as model parameters and training metrics, require verification after download.
National Park Service GIS layers compiled for a water quality inventory report. The data includes locations of monitoring stations, industrial discharges, drinking intakes, gages, and impoundments from six EPA databases. Base layers such as roads, hydrography, and political boundaries are generally at a 1:100,000 scale.
10,000 simulated games of the board game Machi Koro, generated by a neural network and reinforcement learning AI. Each row represents the game state at the beginning of a turn, with variables tracking player coins, constructed properties, and win conditions. The data was created to analyze game strategy and property usefulness.
Replication data supports a study on the relationship between artificial intelligence adoption intensity and green innovation expansion in Chinese listed companies. The dataset covers empirical research indicators from 2014 to 2022. It was authored by Ji Longteng and is hosted by Harvard Dataverse.
PhyslicePPO_artifacts is a dataset published on Kaggle. The title suggests it contains artifacts from training a reinforcement learning agent using the PPO algorithm. The dataset's specific content, scale, and origin are not detailed in the available metadata.
TRL is a dataset for training language models with reinforcement learning, published on Kaggle. The dataset likely contains training data and reward signals for aligning transformer models. Its specific content, size, and authorship require verification after download.
A dataset of synthetic healthcare appointment records focused on no-show events. It was published on Kaggle, but the author, organization, and specific creation date are unknown. The number of rows, columns, and file formats are also unspecified.
2019-2024 data explores the psychological well-being of researchers and university students, focusing on academic stress, burnout, career satisfaction, and institutional support. The dataset is a policy brief synthesized by an autonomous agent from a Dataverse repository. It likely contains survey or assessment data relevant to social sciences and higher education policy.
ParkRecon3D is a surround-view dataset for parking-aware reconstruction. It contains 40,000 synchronized multi-camera sensor frames and 60,000 human-annotated parking-slot labels from four fisheye cameras. The data was collected in four representative underground parking scenes.
Berkeley Gnm Sac Son contains 241,059 frames across 2,955 episodes of robotic task data recorded at 10 FPS. Created by lerobot and updated in March 2026, the collection is structured for the LeRobot v3.0 codebase and includes synchronized video and tabular data.
The London Solar Opportunity Map, developed by the Mayor of London with UCL's Energy Institute and Centre for Advanced Spatial Analysis, identifies potential sites for solar panel and storage installation across London. It provides initial electricity generation estimates based on LiDAR data interpretation from the Environment Agency. The current version uses building outlines from 2017 and solar potential figures derived from LiDAR data collected between March 2006 and January 2016.