Intelligent Computing and Mathematical Physics: Robots, Security Games, Quantum Algorithms and Symbolic Computing

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1671

Special Issue Editors


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Guest Editor
School of Automation and Software Engineering, Shanxi University, Taiyuan 030013, China
Interests: symbol calculation; neural network model; intelligent computing; partial differential equation; mathematical physics

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Guest Editor
School of Software Technology and Key Laboratory for Ubiquitous Network and Service Software, Dalian University of Technology, Dalian 116620, China
Interests: applied mathematics; information systems (business informatics); computer communications (networks); computer security and reliability
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Special Issue Information

Dear Colleagues,

We aim to attract diverse researchers, academics, designers, and others to discuss these issues from various perspectives. This Special Issue invites original submissions not under consideration elsewhere. Authors are requested to contribute essays on innovative and significant scientific contributions, current research initiatives, experimental results, and recent advancements relevant to the following topics:

  • Symbol calculation;
  • Neural network model;
  • Intelligent computing;
  • Partial differential equation;
  • Mathematical physics;
  • Robotics;
  • Dynamics;
  • Control;
  • Numerical simulation;
  • Artificial intelligence;
  • Transition of turbulence;
  • Security game;
  • Bi/tri-level programming;
  • Facility location;
  • Emergency management;
  • Meta-heuristic algorithm;
  • Quantum algorithm;
  • Quantum error correction;
  • Quantum machine learning.

We look forward to receiving your contributions.

Dr. Runfa Zhang
Prof. Dr. Mingchu Li
Guest Editors

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Keywords

  • symbol calculation
  • neural network model
  • intelligent computing
  • partial differential equation
  • mathematical physics
  • robotics
  • dynamics
  • control
  • numercial simulation
  • artificial intelligence
  • transition of turbulence
  • security game
  • bi/tri-level programming
  • facility location
  • emergency management
  • meta-heuristic algorithm
  • quantum algorithm
  • quantum error correction
  • quantum machine learning

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Published Papers (1 paper)

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Research

28 pages, 8515 KiB  
Article
Signaling Security Games with Attack Planner Deception
by Santing He, Mingchu Li and Runfa Zhang
Mathematics 2024, 12(16), 2532; https://doi.org/10.3390/math12162532 - 16 Aug 2024
Viewed by 1238
Abstract
This paper studies a class of attack behavior in which adversaries assume the role of initiators, orchestrating and implementing attacks by hiring executors. We examine the dynamics of strategic attacks, modeling the initiator as an attack planner and constructing the interaction with the [...] Read more.
This paper studies a class of attack behavior in which adversaries assume the role of initiators, orchestrating and implementing attacks by hiring executors. We examine the dynamics of strategic attacks, modeling the initiator as an attack planner and constructing the interaction with the defender within a defender–attack planner framework. The individuals tasked with executing the attacks are identified as attackers. To ensure the attackers’ adherence to the planner’s directives, we concurrently consider the interests of each attacker by formulating a multi-objective problem. Furthermore, acknowledging the information asymmetry where defenders have incomplete knowledge of the planners’ payments and the attackers’ profiles, and recognizing the planner’s potential to exploit this for strategic deception, we develop a defender–attack planner model with deception based on signaling games. Subsequently, through the analysis of the interaction between the defender and planner, we refine the model into a tri-level programming problem. To address this, we introduce an effective decomposition algorithm leveraging genetic algorithms. Ultimately, our numerical experiments substantiate that the attack planner’s deceptive strategy indeed yield greater benefits. Full article
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