Special Issue "Algorithmic Game Theory 2020"

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Analysis of Algorithms and Complexity Theory".

Deadline for manuscript submissions: closed (31 December 2020).

Special Issue Editors

Prof. Tami Tamir
E-Mail Website
Guest Editor
Efi Arazi School of Computer Science, The Interdisciplinary Center, Herzliya, Israel.
Interests: algorithmic game theory; resource allocation problems; approximation algorithms
Prof. Dr. Vittorio Bilò
E-Mail Website
Guest Editor
Department of Mathematics and Physics “Ennio De Giorgi”, University of Salento, Lecce, Italy
Interests: algorithmic game theory; computational social choice; computational complexity and design of efficient algorithms; interconnection networks

Special Issue Information

Dear Colleagues,

Algorithmic game theory (AGT) combines algorithmic thinking with game-theoretic, or, more generally, economic concepts. The study of AGT is motivated by the rise of decentralized computer networks, such as the Internet—that are not controlled by a single central authority, but emerged from the complex interaction between multiple self-interested agents, such as network operators, service providers, users, etc. These agents act in varying degrees of collaboration and competition. 

We invite you to submit high-quality papers to this Special Issue on “Algorithmic Game Theory”. Areas of interest include, but are not limited to the following:

  • Solution concepts in game theory
  • Efficiency of equilibria and price of anarchy
  • Complexity classes in game theory
  • Computational aspects of equilibria
  • Repeated games and convergence of dynamics
  • Algorithmic mechanism design
  • Coalitions, coordination, and collective action
  • Network games and graph-theoretic aspects of social networks
  • Cost-sharing algorithms and analysis
  • Computing with incentives
  • Auction design and analysis

Prof. Tami Tamir

Prof. Vittorio Bilò
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. Algorithms 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 1400 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

Open AccessArticle
Equilibrium Inefficiency and Computation in Cost-Sharing Games in Real-Time Scheduling Systems
Algorithms 2021, 14(4), 103; https://0-doi-org.brum.beds.ac.uk/10.3390/a14040103 - 25 Mar 2021
Viewed by 371
Abstract
We study cost-sharing games in real-time scheduling systems where the server’s activation cost in every time slot is a function of its load. We focus on monomial cost functions and consider both the case when the degree is less than one (inducing positive [...] Read more.
We study cost-sharing games in real-time scheduling systems where the server’s activation cost in every time slot is a function of its load. We focus on monomial cost functions and consider both the case when the degree is less than one (inducing positive congestion effect for the jobs) and when it is greater than one (inducing negative congestion effect for the jobs). For the former case, we provide tight bounds on the price of anarchy, and show that the price of anarchy grows to infinity as a polynomial of the number of jobs in the game. For the latter, we observe that existing results provide constant and tight (asymptotically in the degree of the monomial) bounds on the price of anarchy. We then turn to analyze payment mechanism with arbitrary cost-sharing, that is, when the strategy of a player includes also its payment. We show that our mechanism reduces the price of anarchy of games with n jobs and unit server costs from Θ(n) to 2. We also show that, for a restricted class of instances, a similar improvement is achieved for monomial server costs. This is not the case, however, for unrestricted instances of monomial costs, for which we prove that the price of anarchy remains super-constant for our mechanism. For systems with load-independent activation costs, we show that our mechanism can produce an optimal solution which is stable against coordinated deviations. Full article
(This article belongs to the Special Issue Algorithmic Game Theory 2020)
Open AccessArticle
On Nash Equilibria in Non-Cooperative All-Optical Networks
Algorithms 2021, 14(1), 15; https://0-doi-org.brum.beds.ac.uk/10.3390/a14010015 - 09 Jan 2021
Viewed by 502
Abstract
We consider the problem of determining a routing in all-optical networks, in which some couples of nodes want to communicate. In particular, we study this problem from the point of view of a network provider that has to design suitable payment functions for [...] Read more.
We consider the problem of determining a routing in all-optical networks, in which some couples of nodes want to communicate. In particular, we study this problem from the point of view of a network provider that has to design suitable payment functions for non-cooperative agents, corresponding to the couples of nodes wishing to communicate. The network provider aims at inducing stable routings (i.e., routings corresponding to Nash equilibria) using a low number of wavelengths. We consider three different kinds of local knowledge that agents may exploit to compute their payments, leading to three corresponding information levels. Under complete information, the network provider can design a payment function, inducing the agents to reach a Nash equilibrium mirroring any desired routing. If the price to an agent is computed only as a function of the wavelengths used along connecting paths (minimal level) or edges (intermediate level), the most reasonable functions either do not admit Nash equilibria or admit very inefficient ones, i.e., with the largest possible price of anarchy. However, by suitably restricting the network topology, a constant price of anarchy for chains and rings and a logarithmic one for trees can be obtained under the minimal and intermediate levels, respectively. Full article
(This article belongs to the Special Issue Algorithmic Game Theory 2020)
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