Communications of the ACM
Study Shows Co-Operative Robots Learn and Adapt Quickly Through Natural Language
A newly released study concludes that robots can learn and adjust to their surroundings solely via natural language processing.
Credit: CIO Australia
Robots can learn and adjust rapidly to their surroundings solely via natural language processing, according to a study published as part of the International Joint Conference on Artificial Intelligence in Argentina.
The researchers created a dialogue agent for a mobile robot that can be placed within a workplace environment and quickly learn to perform delivery and navigation tasks to assist human workers without needing to be initially trained on a large body of annotated data. The agent automatically induces training examples from conversations it has with people, using a semantic parser to incrementally learn the meaning of previously unseen words. The agent also can conduct multi-entity reasoning while performing navigation tasks. The researchers note this strategy is stronger than keyword search, and is applicable to any context in which robots are assigned high-level goals in natural language.
More than 300 users engaged with the agent via the Amazon Mechanical Turk Web interface and 20 users via a wheeled Segbot in an office. The agent initially clarifies with the user what they mean by a request, prompting the user to ask the question another way so it can learn different ways of saying the same thing.
Future development will concentrate on applying the agent to speech recognition software, with researchers probing whether it can automatically learn to correct consistent speech recognition errors.
From CIO Australia
View Full Article
Abstracts Copyright © 2015 Information Inc., Bethesda, Maryland, USA
No entries found