Special Issue "Information Theory of Decisions and Actions"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: closed (20 December 2021).

Special Issue Editors

Dr. Daniel Port
E-Mail Website
Guest Editor
Associate Professor of Information Technology Management, University of Hawaii, Honolulu, HI 96822, USA
Interests: actionable business analytics; information technology engineering; software engineering economics; IT education
Dr. Rob Hanna
E-Mail Website
Guest Editor
Strategic Planner, Project Support Office, NASA/Jet Propulsion Laboratory, Pasadena, CA 91109, USA
Interests: strategic decision making; risk management; project management; project support; governance; strategy

Special Issue Information

Dear Colleagues,

Individuals, organizations, corporations and governments are in a continual process of making decisions and taking actions based on those decisions. In practice, it is clear that actions and decisions are not one in the same, with context, bias, perception and other factors separating the two. It is also clear that many decisions, even extremely critical decisions, are made with limited information. Exploring the relationship between information that is gathered, analyzed and presented for critical decision making, as well as the relationship to subsequent actions taken after decisions are made, could provide enormous benefit to all decision makers.

Information Theory, with its mathematical treatment of the generation, storage, transmission and reception of information, has provided a basis of understanding that has transformed telecommunications, physics, optics, computer science, engineering, cryptography, biology and economics. We believe that the application of Information Theory (with concepts such as, e.g., capacity and entropy) may provide greater insights into decision making and action.

Decision Theory studies how, in circumstances with different levels of uncertainty, people combine their values and understanding of their environment to select actions and strategies that are most advantageous. Decision Theory is multidisciplinary, working across the fields of psychology, sociology, and philosophy combined with statistics and mathematics to provide a basis of understanding of how individuals arrive at decisions.

The goal of this Special Issue is to share new and innovative methods, techniques and thought processes around treating and analyzing information surrounding and supporting important, critical and high-risk decisions and actions (D&A) in commercial, charitable and government contexts. Of particular interest are Information Theory approaches to enhance decision making in engineering, science, strategy and systems, including dealing with risk, trades, competing options, policy and governance. The applications of Information Theory in decision making is broad, to say the least. We hope this Special Issue will provide tangible value (techniques, processes, procedures, analyses, etc.) for decision makers and their teams as they work to support critical decisions.

Potential topics include, but are not limited to, the following:

  • Preparation, evaluation, quality, value or availability of information for D&A;
  • Information Theory with respect to risk informed, high risk or critical import D&A;
  • Information associated with engineering design evaluation, trades, options and competition;
  • Information and strategic D&A in the business, political or management domains;
  • Information and tactical D&A for safety, optimization or process improvement;
  • Information and D&A for project management or systems engineering;
  • How information availability, timing or utilization affects D&A;
  • The effect of bias on information and D&A;
  • Assurance of D&A and subsequent confidence in future decisions;
  • The balance of holism and specialization in D&A.

Dr. Daniel Port
Dr. Rob Hanna
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • information theory
  • decision theory
  • decision and actions
  • strategic decision making
  • decision analysis

Published Papers (1 paper)

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A Novel Interval-Valued q-Rung Dual Hesitant Linguistic Multi-Attribute Decision-Making Method Based on Linguistic Scale Functions and Power Hamy Mean
Entropy 2022, 24(2), 166; https://0-doi-org.brum.beds.ac.uk/10.3390/e24020166 (registering DOI) - 22 Jan 2022
The interval-valued q-rung dual hesitant linguistic (IVq-RDHL) sets are widely used to express the evaluation information of decision makers (DMs) in the process of multi-attribute decision-making (MADM). However, the existing MADM method based on IVq-RDHL sets has obvious shortcomings, i.e., the operational rules [...] Read more.
The interval-valued q-rung dual hesitant linguistic (IVq-RDHL) sets are widely used to express the evaluation information of decision makers (DMs) in the process of multi-attribute decision-making (MADM). However, the existing MADM method based on IVq-RDHL sets has obvious shortcomings, i.e., the operational rules of IVq-RDHL values have some weaknesses and the existing IVq-RDHL aggregation operators are incapable of dealing with some special decision-making situations. In this paper, by analyzing these drawbacks, we then propose the operations for IVq-RDHL values based on a linguistic scale function. After it, we present novel aggregation operators for IVq-RDHL values based on the power Hamy mean and introduce the IVq-RDHL power Hamy mean operator and IVq-RDHL power weighted Hamy mean operator. Properties of these new aggregation operators are also studied. Based on these foundations, we further put forward a MADM method, which is more reasonable and rational than the existing one. Our proposed method not only provides a series of more reasonable operational laws but also offers a more powerful manner to fuse attribute values. Finally, we apply the new MADM method to solve the practical problem of patient admission evaluation. The performance and advantages of our method are illustrated in the comparative analysis with other methods. Full article
(This article belongs to the Special Issue Information Theory of Decisions and Actions)
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