13th EAI International Conference on Game Theory for Networks ( GameNets)

13th EAI International Conference on Game Theory for Networks ( GameNets)

March 17– 18, 2025

Venue: Magdalene College, Cambridge, United Kingdom

https://gamenets.eai-conferences.org/2025/

Description

Game theory is a multi-agent decision theory, which provides a mathematical theory tool to study the complex interactions between interdependent rational players and predict strategic choices. Applying game theory in the context of networks provides insights into distributed systems in general. 

Game theoretic models can help us understand and evaluate the performance of complex networked systems that cannot be completely modeled using traditional optimization tools. It helps analyze and address the performance of networks. In communication systems, e.g. wireless networks, vehicular communications, etc., game theory aids in understanding congestion analysis, resource management, and network design as well as providing strategic decisions for network security and resilience. It plays a crucial role in transportation networks, helping determine traffic equilibrium and strategic behavior. In social networks, game theory aids in studying the spread of information and influence and assists in understanding multi-agent games that arise in contexts such as diplomacy.  Game theory also furthers our understanding of the economics of networks, including the study of spectrum auctions, network pricing as well as the study of e-commerce markets. Game theory provides a rich set of techniques including strategic games, cooperative games, collusion strategies and collusion detection, mechanism design, price of anarchy, and computation and analysis of equilibrium.

 Given the importance of the study of game theory in the context of networks, this conference aims to provide a venue to exchange recent advances in this topic. We look for original and unpublished research works that advance fundamental theories, provide techniques, or address applications of game theory for solving challenging problems in networks.

Scope and Topics

Papers presenting new and original research on game theory as applied broadly to networks are sought. Theoretical research papers as well as research in game theory motivated by network applications are encouraged. Typical, but not exclusive, topics of interest include:

– Game theory for networks, including wireless and vehicular networks.

– Congestion analysis and network design

– Traffic networks and equilibria

– Mechanism Design for Networks

– Game theory for social and biological networks

– Network pricing and resource allocation

– Game theory as applied to e-commerce and economic networks

– Game theory for emerging technologies

– Multi-Agent Reinforcement Learning

– Fairness in Resource Allocation

– Cooperative and Coalition games

– Collusion detection approaches

– Game theory for network security/resilience

– Approaches for Multi-agent games (e.g., Diplomacy)

Key Note Speakers:

Tamer Basar: UIUC

Michal Feldman: Tel-Aviv University

Sanjeev Goyal, Cambridge University

Deadlines

Full Paper Submission deadline: 15th October, 2024.

Notification deadline: 15th December, 2024

Camera-ready deadline: 15th January, 2025.

Publication

All accepted papers will be published in the Springer LNICST series and made available through the SpringerLink Digital Library (indexed by Scopus, ACM Digital Library, dblp, Google Scholar). 

Authors of selected papers will be invited to submit an extended version to:

1. ACM Transactions on Economics and Computation: https://dl.acm.org/journal/teac 

2. ACM Journal on Autonomous Transportation Systems: https://dl.acm.org/journal/jats 

Paper Submission

All submitted papers must be unpublished and not be submitted for publication elsewhere. Papers should be submitted through Easy Chair system, and have to comply with the Springer format (see Author’s kit section on the website).

Regular papers should be up to 14 pages in length as per Springer format. Additional material for review may be added as an appendix and will be read at the discretion of the TPC.

Review Process

All conference papers will undergo a thorough peer review process prior to the final decision and publication. This process is facilitated by experts in the Technical Program Committee during a dedicated conference period. All review assignments are ultimately decided by the responsible Technical Program Committee Members while the Technical Program Committee Chairs are responsible for the final acceptance selection.

Committees

Steering Committee

Chair

Victor C.M. Leung, The University of British Columbia, Canada

Members

Arumugam Nallanathan, Queen Mary University of London, U.K

Organizing Committee

General Chair:

Sanjiv Kapoor, Professor, Dept. of Computer Science, Illinois Tech, Chicago, USA 

Program Chairs

Vaneet Aggarwal, Professor, Purdue University, USA

Tobias Harks, Professor, Univ Passau, Germany

Technical Program Committee

Tami Tamir, Reichman University, Israel

Washim Mondal, Indian Institute of Technology Kanpur, India

Pascal Lenzner, Hasso-Plattner-Institute Potsdam, Germany

Martin Gairing, University of Liverpool, UK

Arnob Ghosh, New Jersey Institute of Technology, USA

Marc  Schroder, Maastricht University, Netherlands

Randall Berry, Northwestern University, USA

Duong Nguyen, Arizona State University, USA 

Shweta Jain, Indian Institute of Technology, India

Guido Schaefer, CWI Amsterdam, Netherlands

Xiangyang Li, University of Science and Technology, China

Vittorio Bilo, University of Salento, Italy

Kevin Schewior, University of Southern Denmark, Denmark

S Sivaranjani, University of Notre Dame, USA

Eirini Eleni, University of New Mexico, USA

Jason Marden, UCSB, USA

Anis Elgabli, KFUPM, KSA

Dario Paccagnan, Imperial College London, UK

Parinaz Naghizadeh, University of California, San Diego, USA

Richard Ma, National University of Singapore, Singapore

Information Processing & Management (Impact Factor: 7.4)Special Issue on “Causal Reasoning in Language Models”

This is Michal Ptaszynski from Kitami Institute of Technology, Japan.

We are accepting papers for the Information Processing & Management (IP&M) (IF: 7.4) journal Special Issue on “Causal Reasoning in Language Models”.

The submission closes on March 31, 2025, but your paper will be reviewed immediately after submission and will be published as soon as it is accepted.

We hope you will consider submitting your paper.
https://www.sciencedirect.com/journal/information-processing-and-management/about/call-for-papers#causal-reasoning-in-language-models

Best regards,

Michal PTASZYNSKI, Ph.D., Associate Professor
Text Information Processing Laboratory
Kitami Institute of Technology,
165 Koen-cho, Kitami, 090-8507, Japan
TEL/FAX: +81-157-26-9327
michal@mail.kitami-it.ac.jp

============================================
Journal: Information Processing & Management (Impact Factor: 7.4)
Special Issue on “Causal Reasoning in Language Models”

Guest Editors:
– Michal Ptaszynski (Kitami Institute of Technology), michal@mail.kitami-it.ac.jp
– Rafal Rzepka (Hokkaido University)
– Rafal Urbaniak (University of Ghent)

Introduction:
Causal reasoning is a fundamental cognitive ability that allows humans to understand the cause-and-effect relationships in the world around them. Integrating causal reasoning capabilities into language models has emerged as a promising research direction, with significant implications for natural language processing (NLP) and artificial intelligence (AI) applications. The special issue on “Causal Reasoning in Language Models” aims to provide a platform for researchers to explore the latest advancements and challenges in this burgeoning field.

Topics of Interest:
We invite submissions on a wide range of topics related to causal reasoning in language models, including but not limited to:
– Causal inference techniques in natural language processing
– Evaluating causal understanding in large language models
– Causal representations in transformer architectures
– Counterfactual reasoning capabilities of language models
– Causal discovery from unstructured text data
– Incorporating causal knowledge into language model pre-training
– Causal explanation generation using language models
– Bias and fairness in causal language modeling
– Causal reasoning for improved few-shot and zero-shot learning
– Temporal and event causal reasoning in language models
– Theoretical frameworks for representing causal knowledge in language models
– Methodologies for incorporating causal reasoning into NLP tasks, such as text generation, question answering, and summarization
– Evaluation metrics and benchmarks for assessing the performance of causal reasoning models in language understanding tasks
– Applications of causal reasoning in real-world scenarios, including healthcare, finance, social media analysis, and more
– Ethical considerations and societal implications of integrating causal reasoning into AI systems
– Interdisciplinary approaches that combine insights from linguistics, cognitive science, and computer science to advance causal reasoning in language models

Submission Guidelines:
Papers submitted to this special issue must adhere to the submission guidelines of Information Processing & Management. Manuscripts should be original, unpublished works not currently under review elsewhere. All submissions will undergo a rigorous peer review process to ensure high quality and relevance to the special issue.

Important Dates:
– Submission opens: 2024-7-31
– Submission closes: 2025-3-31

Submission Instructions:
Submit your manuscript to the Special Issue category (VSI: CAUSAL LLMs) through the online submission system of Information Processing & Management (https://www.editorialmanager.com/ipm/default.aspx). All the submissions should follow the general author guidelines of Information Processing & Management (https://www.sciencedirect.com/journal/information-processing-and-management). For any inquiries or further information, please contact the Managing Guest Editor at michal@mail.kitami-it.ac.jp.

Conclusion:
We encourage researchers from academia and industry to contribute their latest findings and innovations to this special issue. By bringing together a collection of high-quality papers on causal reasoning in language models, we aim to advance the state of the art in NLP, foster interdisciplinary collaborations, and pave the way for future developments in AI.

We look forward to your contributions.

Sincerely,

Michal Ptaszynski, in the name of all Guest Editors

CFP Track Accessible Devices and Technologies (ADT ’25) – ACM SAC 2025

Track on Accessible Devices and Technologies (ADT ‘25)

Sicily, Italy, March 31 – April 4, 2025

Part of the 40th ACM/SIGAPP Symposium on Applied Computing (SAC ‘25)

https://sites.google.com/view/adt-sac-2025

https://www.sigapp.org/sac/sac2025/

Theme and Scope

Modern devices and technologies can represent a digital barrier for users with disabilities, but they can be exploited to become enabling tools for them. Accessibility of devices and technologies is a critical topic to allow inclusion of all users, especially due to the European laws that impose accessibility for new products and the definition of an updated version of WCAG (Web Accessibility Guidelines). This track invites scientists, engineers, and decision-makers from government, industry, and academia to present technical papers on their research and development results in areas of accessibility.

This track can interest many researchers since it would give the chance to face a wide range of topics, i.e., web or mobile technologies, with different points of view, taking into account specific technological constraints and digital barriers. It is well-known that the so-called “curb cut effect” can be applied to any technological and digital context (in terms of devices, content, and services): technologies that were originally meant to benefit people with disabilities can help any other users. Moreover, the history and the evolution of several technologies have been influenced and/or motivated by the special needs of people with disabilities. 

We welcome submission on a wide range of topics, including but not limited to:

  • Accessible devices/assistive technologies: assistive technologies refer to all the assistive, adaptive, and rehabilitative devices for people with disabilities that enable users to perform tasks they were formerly unable to accomplish. On the one hand, the widespread diffusion of new devices and technologies stimulates researchers to find and apply new solutions to make them accessible to anyone. On the other hand, experiences in accessibility-related fields have been exploited and have provided benefits to users equipped with non-conventional devices when they emerged in the market.

  • Accessible solutions for e-learning, e-commerce, e-banking, etc: e-services and content often require specific technologies, being bounded by specific constraints when accessed by people with disabilities equipped with assistive technologies. Specific interaction modalities may affect interactive service access, while richness and quantity of content may affect the users’ ability to process information. 

  • Accessible content: e-books, accessible TV, accessible broadcasting, etc.

  • Accessibility of games.

  • AI for Accessibility: AI can be exploited both for personalization (i.e., integrating AI-based personalization to support specific and special needs) and “enabler” (i.e., exploiting LLM to support the creation of accessible applications).

Submission Guidelines

We would like to invite authors to submit papers on research on the Accessibility area, with particular emphasis on assessing the current state of the art and identifying future directions. Original papers addressing any of the listed topics of interest (or related topics) will be considered. Each submitted paper will be fully refereed and undergo a double-blind review process by at least three referees. Accepted papers will be included in the ACM SAC 2025 proceedings and published in the ACM digital library, being indexed by Thomson ISI Web of Knowledge and Scopus. 

The track accepts full papers (max 8 pages), posters (max 2 pages), and SRC abstracts (max 2 pages). Submissions should be properly anonymized to facilitate blind reviewing. Papers that will receive high reviews (that is acceptable by reviewer standard) but will not be accepted due to space limitations can be invited for poster session. Authors of accepted papers must be prepared to sign a copyright statement and must pay the registration fee and guarantee that their paper will be presented at the conference. No-show of scheduled papers will result in excluding the papers from the ACM Digital Library. 

See the track website https://sites.google.com/view/adt-sac-2025 for more details. 

Important Dates

  • September 20, 2024, 11:59 PM (UTC+0.00): Submission of regular papers and SRC research abstracts

  • October 30, 2024: Notification of papers, posters, and SRC research abstracts

  • November 29, 2024: Camera-ready copies of accepted papers

  • December 6, 2024: Authors registration due

Organization

  • Ombretta Gaggi, University of Padua

  • Silvia Mirri, University of Bologna

  • Mike Paciello, AudioEye, WebABLE

  • Catia Prandi, University of Bologna

Submission Portal 

Please submit your contribution through our online submission portal available at https://www.sigapp.org/sac/sac2025/submission.php (regular papers) and https://www.sigapp.org/sac/sac2025/submission_src.php (SRC abstracts).

Contact us

For any inquires regarding the call for papers, please contact gaggi@math.unipd.it.

We look forward to your contributions and to seeing you at the ACM SAC 2025 Conference!

Invitation to Submit Your Research to MedPRAI 2024

Dear Researchers,

We are pleased to invite you to submit your research papers to the upcoming 6th Mediterranean Conference on Pattern Recognition & Artificial Intelligence (MedPRAI 2024), scheduled to be held on October 18-19, 2024, at Istinye University, Istanbul, Turkey. This conference offers a platform for sharing advancements in pattern recognition, artificial intelligence, and related fields.

Paper Submission Deadline: September 10, 2024

Conference Website:

https://medprai.com/

 Submission Link: 

All accepted papers will be published in the Springer book series Lecture Notes in Networks and Systems (LNNS). LNNS is indexed in well-known databases such as EI Compendex, SCOPUS, DBLP, INSPEC, Norwegian Register for Scientific Journals and Series, SCImago, WTI Frankfurt eG, and zbMATH.

 

Please find attached the Call for Papers (CFP) with detailed information on submission guidelines, important dates, and topics of interest.

 

We look forward to your participation and contributions to making MedPRAI 2024 a success.

Regards,

Dr. AKHTAR JAMIL

Associate Professor

Department of Computer Science, 
FAST School of Computing
National University of Computer and Emerging Sciences, 
Islamabad, Pakistan.
Office Tel. (051) 111-128-128;  Ext. 633

FAST University  :   http://isb.nu.edu.pk/

Regards,

Dr. AKHTAR JAMIL

Associate Professor

Department of Computer Science, 
FAST School of Computing
National University of Computer and Emerging Sciences, 
Islamabad, Pakistan.
Office Tel. (051) 111-128-128;  Ext. 633

FAST University  :   http://isb.nu.edu.pk/

CfP: Technical track on Graph Models for Learning and Recognition

Call for Papers

Graph Models for Learning and Recognition (GMLR) Track

The 40th ACM Symposium on Applied Computing (SAC 2025)

March 31 – April 4, 2025 Catania, Italy

https://phuselab.di.unimi.it/GMLR2025/

Important Dates

  • Submission of regular papers and SRC abstracts: September 20, 2024
  • Notification of papers/SRC acceptance/rejection: October 30, 2024
  • Camera-ready copies of accepted papers/SRC: November 29, 2024
  • Author registration due date: December 6, 2024

Motivations and topics

The ACM Symposium on Applied Computing (SAC 2025) has been a primary gathering forum for applied computer scientists, computer engineers, software engineers, and application developers from around the world. SAC 2025 is sponsored by the ACM Special Interest Group on Applied Computing (SIGAPP), and will be held in Catania, Italy. The technical track on Graph Models for Learning and Recognition (GMLR) is the fourth edition and is organized within SAC 2025. Graphs have gained a lot of attention in the pattern recognition community thanks to their ability to encode both topological and semantic information. Despite their invaluable descriptive power, their arbitrarily complex structured nature poses serious challenges when they are involved in learning systems. Some (but not all) of challenging concerns are: a non-unique representation of data, heterogeneous attributes (symbolic, numeric, etc.), and so on.

In recent years, due to their widespread applications, graph-based learning algorithms have gained much research interest. Encouraged by the success of CNNs, a wide variety of methods have redefined the notion of convolution and related operations on graphs. These new approaches have in general enabled  effective training and achieved in many cases better performances than competitors, though at the detriment of computational costs. Typical examples of applications dealing  with graph-based representation are: scene graph generation, point clouds classification, and action recognition in computer vision; text classification, inter-relations of documents or words to infer document labels in natural language processing; forecasting traffic speed, volume or the density of roads in traffic networks, whereas in chemistry researchers apply graph-based algorithms to study the graph structure of molecules/compounds.

This track intends to focus on all aspects of graph-based representations and models for learning and recognition tasks. GMLR spans, but is not limited to, the following topics:

  • Graph Neural Networks: theory and applications

  • Deep learning on graphs

  • Graph or knowledge representational learning

  • Graphs in pattern recognition

  • Graph databases and linked data in AI

  • Benchmarks for GNN

  • Dynamic, spatial and temporal graphs

  • Graph methods in computer vision

  • Human behavior and scene understanding

  • Social networks analysis

  • Data fusion methods in GNN

  • Efficient and parallel computation for graph learning algorithms

  • Reasoning over knowledge-graphs

  • Interactivity, explainability and trust in graph-based learning

  • Probabilistic graphical models

  • Biomedical data analytics on graphs

Submission Guidelines

Authors are invited to submit original and unpublished papers of research and applications for this track. The author(s) name(s) and address(es) must not appear in the body of the paper, and self-reference should be in the third person. This is to facilitate double-blind review. Please, visit the website for more information about submission.

SAC No-Show Policy

Paper registration is required, allowing the inclusion of the paper/poster in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for the paper/poster to be included in the ACM digital library. No-show of registered papers and posters will result in excluding them from the ACM digital library.


Track Chairs

  • Vittorio Cuculo (University of Modena e Reggio Emilia)
  • Alessandro D'Amelio (University of Milan)
  • Giuliano Grossi (University of Milan)
  • Raffaella Lanzarotti (University of Milan)
  • Jianyi Lin (Università Cattolica del Sacro Cuore)

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