• Classified by Topic • Classified by Publication Type • Sorted by Date • Sorted by First Author Last Name • Classified by Funding Source •
Integrated Commonsense Reasoning and Probabilistic Planning.
Shiqi Zhang
and Peter Stone.
In Proceedings of 2017 ICAPS Workshop on Planning and
Robotics, June 2017.
Commonsense reasoning and probabilistic planning are two of the most important research areas in artificial intelligence. This paper focuses on Integrated commonsense Reasoning and probabilistic Planning (IRP) problems. On one hand, commonsense reasoning algorithms aim at drawing conclusions using structured knowledge that is typically provided in a declarative way. On the other hand, probabilistic planning algorithms aim at generating an action policy that can be used for action selection under uncertainty. Intuitively, reasoning and planning techniques are good at ``understanding the world'' and ``accomplishing the task'' respectively. This paper discusses the complementary features of the two computing paradigms, presents the (potential) advantages of their integration, and summarizes existing research on this topic.
@InProceedings{PlanRob17-Zhang,
author = {Shiqi Zhang and Peter Stone},
title = {Integrated Commonsense Reasoning and Probabilistic Planning},
booktitle = {Proceedings of 2017 ICAPS Workshop on Planning and Robotics},
location = {Pittsburgh, PA},
month = {June},
year = {2017},
abstract = {
Commonsense reasoning and probabilistic planning are two
of the most important research areas in artificial intelligence.
This paper focuses on Integrated commonsense Reasoning
and probabilistic Planning (IRP) problems. On one hand,
commonsense reasoning algorithms aim at drawing conclusions
using structured knowledge that is typically provided
in a declarative way. On the other hand, probabilistic planning
algorithms aim at generating an action policy that can be
used for action selection under uncertainty. Intuitively, reasoning
and planning techniques are good at ``understanding
the world'' and ``accomplishing the task'' respectively. This
paper discusses the complementary features of the two computing
paradigms, presents the (potential) advantages of their
integration, and summarizes existing research on this topic.
},
}
Generated by bib2html.pl (written by Patrick Riley ) on Tue Nov 19, 2024 10:24:47