General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail:
    • Journal Metrics:

    • SCImago Journal & Country Rank
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2013 Vol.5(3): 557-561 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2013.V5.749

Collaborative Planning Using Hierarchical Task Network

Teeradaj Racharak

Abstract—Planning is one of the critical components in human being’s decision making processes. It is a reasoning paradigm where people have to choose and organize actions to satisfy their expected outcomes. In the field of Artificial Intelligence, Automated Planning and Scheduling has become an immense research. Collaborative planning is one of the important planning problems as working together through the act of making choices is fundamental for human nature. This fact is reflected in an emergence of collaborative tools for people’s participation. Such tools include social networking sites, instant messengers, email and mailing list, and so on. Unfortunately, these collaborating tools are still functioned based on the notion of human creativity involvement without an automatic planning system. This paper presented the framework to represent collaborative planning problems using HTN formalism, determine the plans, and evaluate the most preferred plan. Three main components are HTN planner(s), Plans validator, and Plan selector. The paper also provided the methodology to solve the problems under the assumption that planning knowledge is decentralized. This is described in terms of communication protocols for decentralized cooperative agents.

Index Terms—Artificial intelligence, collaborative planning representation, htn planning, multi-agent system

Teeradaj Racarak is with the Development Engineer at Octosoft, Thailand, and as a Special Instructor at the Department of Computer Science, Rajamangala University of Technology Thanyaburi, Thailand (e-mail: r.teeradaj@


Cite:Teeradaj Racharak, "Collaborative Planning Using Hierarchical Task Network," International Journal of Computer Theory and Engineering vol. 5, no. 3, pp. 557-561, 2013.

Copyright © 2008-2024. International Association of Computer Science and Information Technology. All rights reserved.