Extracting Action Sequences from Texts Based on Deep Reinforcement Learning

03/07/2018
by   Wenfeng Feng, et al.
0

Extracting action sequences from texts in natural language is challenging, which requires commonsense inferences based on world knowledge. Although there has been work on extracting action scripts, instructions, navigation actions, etc., they require either the set of candidate actions is provided in advance, or action descriptions are restricted in a specific form, e.g., description templates. In this paper, we aim to extract action sequences from texts in free natural language, i.e., without any restricted templates, provided the candidate set of actions is unknown. We propose to extract action sequences from texts based on the deep reinforcement learning framework. Specifically, we view "selecting" or "eliminating" words from texts as "actions", and texts associated with actions as "states". We then build Q-networks to learn the policy of extracting actions and extract plans from the labelled texts. We exhibit the effectiveness of our approach in several datasets with comparison to state-of-the-art approaches, including online experiments interacting with humans.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/14/2015

Deep Reinforcement Learning with a Natural Language Action Space

This paper introduces a novel architecture for reinforcement learning wi...
research
02/15/2022

Text-Based Action-Model Acquisition for Planning

Although there have been approaches that are capable of learning action ...
research
12/04/2018

Playing Text-Adventure Games with Graph-Based Deep Reinforcement Learning

Text-based adventure games provide a platform on which to explore reinfo...
research
02/04/2019

The Natural Language of Actions

We introduce Act2Vec, a general framework for learning context-based act...
research
06/12/2016

Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads

We introduce an online popularity prediction and tracking task as a benc...
research
11/17/2022

Planning with Large Language Models via Corrective Re-prompting

Extracting the common sense knowledge present in Large Language Models (...
research
07/17/2023

Automated Action Model Acquisition from Narrative Texts

Action models, which take the form of precondition/effect axioms, facili...

Please sign up or login with your details

Forgot password? Click here to reset