- AI2-THOR
AI2-THOR now supports headless rendering, making it easier and more accessible to use on computing clusters
- AI2-THOR - AllenAI
By default, AI2-THOR does not work out of the box with Google Colab, as it requires the use of Xorg for AI2-THOR to work
- AI2-THOR Publications - AllenAI
AI2-THOR enables research in many different domains including but not limited to deep reinforcement learning, imitation learning, learning by interaction, planning, visual question answering, unsupervised representation learning, object detection and segmentation, and learning models of cognition
- Demo - AllenAI
Interactive Demo for the AI2-THOR Framework RoboTHOR includes 89 apartments, distributed as 60 training scenes, 15 validation scenes, and 14 testing scenes (which also exist in the real world) Scenes are numbered by WallConfiguration_i, where scenes that share the same first number share the same wall layout The goal of RoboTHOR is to study sim2real transfer
- AI2-THOR - AllenAI
A scene within AI2-THOR represents a virtual room that an agent can navigate and interact in There are 4 scene Categories, each with 30 unique scenes within them: Kitchen, Living Room, Bedroom, Bathroom
- RoboTHOR - AllenAI
RoboTHOR is an environment within the AI2-THOR framework, designed to develop embodied AI agents It consists of a series of scenes in simulation with counterparts in the physical world
- iTHOR - AllenAI
iTHOR is an environment within the AI2-THOR framework, which includes a set of interactive objects and scenes and provides accurate modeling of the physics of the world
- AI2-THOR - AllenAI
By default, AI2-THOR executes high-level actions that provide a response from the environment after the action completes execution For instance, if the agent successfully executes an
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