Augmenting Knowledge through Statistical, Goal-oriented Human-Robot Dialog

07/08/2019
by   Saeid Amiri, et al.
0

Some robots can interact with humans using natural language, and identify service requests through human-robot dialog. However, few robots are able to improve their language capabilities from this experience. In this paper, we develop a dialog agent for robots that is able to interpret user commands using a semantic parser, while asking clarification questions using a probabilistic dialog manager. This dialog agent is able to augment its knowledge base and improve its language capabilities by learning from dialog experiences, e.g., adding new entities and learning new ways of referring to existing entities. We have extensively evaluated our dialog system in simulation as well as with human participants through MTurk and real-robot platforms. We demonstrate that our dialog agent performs better in efficiency and accuracy in comparison to baseline learning agents. Demo video can be found at https://youtu.be/DFB3jbHBqYE

READ FULL TEXT

page 1

page 6

research
05/20/2020

Learning and Reasoning for Robot Dialog and Navigation Tasks

Reinforcement learning and probabilistic reasoning algorithms aim at lea...
research
04/25/2021

Dynamic generation and refinement of robot verbalization

With a growing number of robots performing autonomously without human in...
research
05/25/2022

Understanding Natural Language in Context

Recent years have seen an increasing number of applications that have a ...
research
11/20/2020

Towards Abstract Relational Learning in Human Robot Interaction

Humans have a rich representation of the entities in their environment. ...
research
06/13/2023

Ontological component-based description of robot capabilities

A key aspect of a robot's knowledge base is self-awareness about what it...
research
05/13/2020

Towards Automatic building of Human-Machine Conversational System to support Maintenance Processes

Companies are dealing with many cognitive changes with the introduction ...
research
04/21/2023

Which Factors Predict the Chat Experience of a Natural Language Generation Dialogue Service?

In this paper, we proposed a conceptual model to predict the chat experi...

Please sign up or login with your details

Forgot password? Click here to reset