Dynamic Games and Applications

Scope & Guideline

Unraveling Complex Strategies Across Disciplines

Introduction

Immerse yourself in the scholarly insights of Dynamic Games and Applications with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN2153-0785
PublisherSPRINGER BIRKHAUSER
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 2011 to 2024
AbbreviationDYN GAMES APPL / Dyn. Games Appl.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address233 SPRING STREET, 6TH FLOOR, NEW YORK, NY 10013

Aims and Scopes

Dynamic Games and Applications focuses on the intersection of dynamic game theory and various applications across multiple domains. The journal aims to explore theoretical advancements in game dynamics while providing practical insights and solutions to complex real-world problems.
  1. Dynamic Game Theory Development:
    The journal emphasizes the development of dynamic game theory, including both deterministic and stochastic frameworks, to analyze interactions among rational decision-makers over time.
  2. Application to Social and Economic Systems:
    Research often applies game-theoretic models to social, economic, and environmental issues, highlighting the journal's commitment to addressing real-world challenges through mathematical rigor.
  3. Multi-agent Systems and Cooperative Games:
    A significant focus is on multi-agent systems, exploring cooperative and non-cooperative strategies, which contribute to understanding complex interactions in various fields such as economics, ecology, and network theory.
  4. Epidemic Modeling and Public Health:
    The journal has carved a niche in applying dynamic games to epidemic modeling and public health, examining how strategic interactions impact disease spread and control measures.
  5. Robustness and Learning in Games:
    Research in this area explores how players adapt their strategies in dynamic environments, focusing on learning mechanisms and robustness of game-theoretic solutions.
Recent publications in Dynamic Games and Applications reveal several trending and emerging themes that reflect the evolving landscape of research in dynamic game theory and its applications.
  1. Mean Field Games:
    The study of mean field games has gained traction, focusing on large populations of players and their collective behaviors, which is crucial for understanding phenomena in economics and social sciences.
  2. Epidemic Control Strategies:
    Research exploring game-theoretic approaches to epidemic control, particularly during and after the COVID-19 pandemic, has surged, emphasizing the relevance of strategic decision-making in public health.
  3. Dynamic Resource Management:
    There is an increasing interest in dynamic resource management games, which address sustainability and optimal resource allocation in various contexts, including environmental economics and ecological systems.
  4. Stochastic and Robust Game Models:
    The emergence of stochastic and robust game models highlights the need for solutions that account for uncertainty and variability in player behaviors and environmental conditions.
  5. Networked Game Dynamics:
    The analysis of games on networks, including social and communication networks, is becoming more prevalent, reflecting the complexities of interactions in interconnected systems.

Declining or Waning

While Dynamic Games and Applications continues to explore a wide range of topics, certain themes have seen a decline in publication frequency or focus over the years. This section highlights those waning scopes.
  1. Static Game Models:
    There has been a noticeable decrease in the publication of static game models, reflecting a shift towards more dynamic and time-dependent analyses that better capture the complexity of real-world interactions.
  2. Single-agent Decision Making:
    Research centered on single-agent decision-making frameworks has become less prominent, as the journal's emphasis has shifted towards multi-agent interactions and cooperative dynamics.
  3. Basic Nash Equilibrium Concepts:
    While foundational concepts of Nash equilibria are still relevant, there is a decreasing trend in papers solely focused on basic Nash equilibrium analyses without the integration of dynamic or evolutionary aspects.

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