Abstract
dc:description.abstractThis thesis introduces a Watch-And-Help (WAH) challenge and a multi-agent environment for testing social intelligence in multiple agents. In the challenge, an AI agent needs to help a human-like agent perform a complex household task efficiently. To succeed, the AI agent needs to i) understand the underlying goal of the task by watching a single demonstration of the human-like agent performing the same task (social perception), and ii) coordinate with the human-like agent to solve the task in an unseen environment as fast as possible (human-AI collaboration). For this challenge, we build VirtualHome-Social, a multi-agent household environment, and provide a benchmark including both planning and learning based baselines. Experimental results demonstrate that in order to achieve success in the challenge, an AI agent has to accurately understand and predict the human-like agent's behaviors, and adapt its collaborative plan accordingly in novel environments.
Degree
thesis:*- Name thesis:degree_name
- Master
- Department dc:contributor.department
- Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2020
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Li, Shuang,S.M.Massachusetts Institute of Technology.
- Advisor dc:contributor.advisor
-
- Antonio Torralba.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- https://hdl.handle.net/1721.1/129367
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/129367