Imitation Learning Datasets: A Toolkit For Creating Datasets, Training Agents and Benchmarking

arXiv:2403.00550v1 Announce Type: new
Abstract: Imitation learning field requires expert data to train agents in a task. Most often, this learning approach suffers from the absence of available data, which results in techniques being tested on its dataset. Creating datasets is a cumbersome process requiring researchers to train expert agents from scratch, record their interactions and test each benchmark method with newly created data. Moreover, creating new datasets for each new technique results in a lack of consistency in the …

agents arxiv benchmarking cs.ai cs.lg datasets imitation learning toolkit training type