  The problem of task planning for artificial agents remains largely unsolved.
While there has been increasing interest in data-driven approaches for the
study of task planning for artificial agents, a significant remaining
bottleneck is the dearth of large-scale comprehensive task-based datasets. In
this paper, we present ActioNet, an interactive end-to-end platform for data
collection and augmentation of task-based dataset in 3D environment. Using
ActioNet, we collected a large-scale comprehensive task-based dataset,
comprising over 3000 hierarchical task structures and videos. Using the
hierarchical task structures, the videos are further augmented across 50
different scenes to give over 150,000 video. To our knowledge, ActioNet is the
first interactive end-to-end platform for such task-based dataset generation
and the accompanying dataset is the largest task-based dataset of such
comprehensive nature. The ActioNet platform and dataset will be made available
to facilitate research in hierarchical task planning.
