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Entropy
Special Issues
Information Theory for Control, Games, and Decision Problems
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Information Theory for Control, Games, and Decision Problems

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 (31 October 2019) | Viewed by 5254

Special Issue Editors

Prof. Dr. Tobias Oechtering

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Guest Editor
KTH Royal Institute of Technology, School of Electrical Engineering, Communication Theory Department, Osquldas väg 10, 10044 Stockholm, Sweden
Interests: information theory; physical layer security and privacy; statistical signal processing; communications; networked control
Special Issues, Collections and Topics in MDPI journals
Dr. Maël Le Treust

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Guest Editor
ETIS UMR 8051, Université Paris Seine, Université Cergy-Pontoise, ENSEA, CNRS 6 av. du Ponceau, 95014 CERGY, France
Interests: empirical coordination; shannon theory; game theory; wireless communications; repeated game with imperfect monitoring; source and channel coding; physical layer security
Prof. Dr. Serdar Yuksel

E-Mail Website
Guest Editor
Department of Mathematics and Statistics, Queen's University, Kingston, ON K7L 3N6, Canada
Interests: stochastic control; information theory; networked and decentralized control, stochastic dynamical systems

Special Issue Information

Dear Colleagues,

Originally Shannon's information theory was developed deriving fundamental bounds on the rate of communication regardless the application, thus semantic aspects of the communication were not taken into account. This has led to specific operational definitions that are in particular not suitable for time-sensitive applications and setups. 

Since optimality is not guaranteed for separating processing for communication and the application, typically upper and lower bounds on performance have been derived for specific applications. In particular fundamental results have been obtained in the last years for problems in distributed control and decision theory. This special issue should take up this development and provide the space to for original works dealing with cross-disciplinary problems where information theory is used for (distributed) control problems or decision problems, which may also include problems from operations research. Accordingly, topics of interest include, but are not restricted to, the following

- Interplay between information, control, and/or decision theories

- Information-theoretic methods in game theory

- Signaling games and related problems in networked systems

- Coordination problems under information constraints

- Coding theory for control and decision problems

- Optimal co-design of communication and control for networked control

- Sufficient and necessary conditions on communication requirements for stability

- Entropy in control, dynamical systems and information theory

- Information theoretic security and privacy for control and decision systems

- Quantisation and code design for control/decision problems

- Metric and topological entropy concepts and their applications in control and game theory

Prof. Dr. Tobias Oechtering
Dr. Maël Le Treust
Prof. Dr. Serdar Yuksel
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 submissions that pass pre-check are 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 2600 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.

Published Papers (2 papers)

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Research

20 pages, 335 KiB  
Article
A Survey on Entropy and Economic Behaviour
by Ziv Hellman and Ron Peretz
Entropy 2020, 22(2), 157; https://doi.org/10.3390/e22020157 - 29 Jan 2020
Cited by 5 | Viewed by 2320
Abstract
Entropy plays a significant role in the study of games and economic behaviour in several ways. A decision maker faced with an n-fold repetition of a decision-making problem needs to apply strategies that become increasingly complex as n increases. When several players are [...] Read more.
Entropy plays a significant role in the study of games and economic behaviour in several ways. A decision maker faced with an n-fold repetition of a decision-making problem needs to apply strategies that become increasingly complex as n increases. When several players are involved in selecting strategies in interactive games, bounds on the memories and cognitive capacities of the players can affect possible outcomes. A player who can recall only the last k periods of history is said to have bounded recall of capacity k. We present here a brief survey of results of games played by players with different bounded recall capacities, in particular those indicating surprisingly strong relations between memory and entropy in the study of the min-max values of repeated games with bounded recall. In addition, we consider uses of entropy in measuring the value of information of noisy signal structures, also known as experiments. These are represented by stochastic matrices, with the rows representing states of the world and the columns possible signals. The classic ordering of experiments, due to David Blackwell and based on decision-making criteria, is a partial ordering, which has led to attempts to extend this ordering to a total ordering. If a decision maker has a prior distribution over the states, receipt of a signal yields a posterior. The difference between the entropy of a prior and the expected entropy of the set of possible posteriors has been proposed as a natural extension of the Blackwell ordering. We survey this alongside the theory of rational inattention, which posits that, since individuals have limited attention, they do not always follow every single piece of economic news in planning their economic behaviour. By modelling attention limits as finite channel capacity in the sense of Shannon, economists have developed a theory that explains a range of observed economic behavioural phenomena well. Full article
(This article belongs to the Special Issue Information Theory for Control, Games, and Decision Problems)
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32 pages, 608 KiB  
Article
Zero-Delay Multiple Descriptions of Stationary Scalar Gauss-Markov Sources
by Andreas Jonas Fuglsig and Jan Østergaard
Entropy 2019, 21(12), 1185; https://doi.org/10.3390/e21121185 - 01 Dec 2019
Cited by 1 | Viewed by 2205
Abstract
In this paper, we introduce the zero-delay multiple-description problem, where an encoder constructs two descriptions and the decoders receive a subset of these descriptions. The encoder and decoders are causal and operate under the restriction of zero delay, which implies that at each [...] Read more.
In this paper, we introduce the zero-delay multiple-description problem, where an encoder constructs two descriptions and the decoders receive a subset of these descriptions. The encoder and decoders are causal and operate under the restriction of zero delay, which implies that at each time instance, the encoder must generate codewords that can be decoded by the decoders using only the current and past codewords. For the case of discrete-time stationary scalar Gauss—Markov sources and quadratic distortion constraints, we present information-theoretic lower bounds on the average sum-rate in terms of the directed and mutual information rate between the source and the decoder reproductions. Furthermore, we show that the optimum test channel is in this case Gaussian, and it can be realized by a feedback coding scheme that utilizes prediction and correlated Gaussian noises. Operational achievable results are considered in the high-rate scenario using a simple differential pulse code modulation scheme with staggered quantizers. Using this scheme, we achieve operational rates within 0.415 bits / sample / description of the theoretical lower bounds for varying description rates. Full article
(This article belongs to the Special Issue Information Theory for Control, Games, and Decision Problems)
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