FW: Call for Papers: AJCAI 2025 – Canberra, Australia (Deadline: 15 July 2025)

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Pascal Bercher

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Jun 26, 2025, 2:45:59 AMJun 26
to planni...@googlegroups.com, 'Jendrik Seipp' via ICAPS Conference, Jing Zhang, Miaomiao Liu, Xin Yu

Dear planning (and AI) community,

 

Please see below a call for papers (note that AJCAI takes place soon(ish) after ICAPS; both in Australia).
(Feel free to forward.)


Best,
Pascal

 

-- 
Dr. Pascal Bercher 

Associate Professor

School of Computing 

College of Systems & Society 

The Australian National University (ANU) 

Canberra, Australia 

Hanna Neumann Building, Level 3, Office 3.36 

T: +61 (0)2 - 612 - 50 322 

W: https://comp.anu.edu.au/people/pascal-bercher/

W: https://bercher.net/

E: pascal....@anu.edu.au

 

 

From: Jing Zhang <Jing....@anu.edu.au>
Date: Thursday, 26 June 2025 at 3:14
pm
To:
Cc: Miaomiao Liu <miaomi...@anu.edu.au>, Xin Yu <xin...@uq.edu.au>
Subject: Call for Papers: AJCAI 2025 – Canberra, Australia (Deadline: 15 July 2025)

Dear Colleagues and Friends,

 

We are pleased to announce that the Australasian Joint Conference on Artificial Intelligence (AJCAI) 2025 (https://ajcai2025.org) will be held in Canberra, Australia, from 1–5 December 2025. The extended submission deadline is 15 July 2025.

On behalf of the Organizing Committee, we cordially invite you to submit your papers to AJCAI 2025. The conference provides an excellent forum for researchers, practitioners, and academics from around the world to share their latest advances and insights in Artificial Intelligence. All accepted papers will be published by Springer in the Lecture Notes in Artificial Intelligence (LNAI) series.

We welcome submissions of original research papers in (but not limited to) the following areas:

  • Agent-based and multi-agent systems
  • AI applications and innovations
  • Cognitive modelling and computer-human interaction
  • Commonsense reasoning
  • Computer vision
  • Constraint satisfaction, search, and optimisation
  • Deep Learning
  • Generative Models
  • Evolutionary computation
  • Explainable AI
  • Fairness, Accountability and Transparency
  • Fuzzy Systems
  • Game playing and interactive entertainment
  • Human-Robot Interaction
  • Information retrieval, integration, and extraction
  • Learning and Reasoning Integration
  • Knowledge acquisition and ontologies
  • Knowledge representation and reasoning
  • Machine learning and data mining
  • Model-based systems
  • Multidisciplinary AI
  • Natural language processing
  • Neural Networks
  • Planning and scheduling
  • Robotics
  • Social Robotics
  • Social choice
  • Uncertainty in AI
  • Web and Information Systems
  • Trustworthy Large Models

 

Keynote speakers include:

·                     Professor Toby Walsh – ARC Laureate Fellow and Scientia Professor of AI, UNSW & CSIRO Data61, Australia

·                     Professor Jing Jiang – School of Computing, Australian National University, Australia

·                     Professor Ling Chen – School of Computer Science, University of Technology Sydney, Australia

·                     Professor Mengjie Zhang – Fellow of the Royal Society of New Zealand, IEEE Fellow, and Professor at Victoria University of Wellington, New Zealand

·                     Associate Professor Nicholas Mattei – Co-Director, Tulane Center of Excellence for Community Engaged AI, Tulane University, USA

More details can be found in the attached Call for Papers and on the official conference website: https://ajcai2025.org

We look forward to receiving your submissions!

Warm regards,

Stephen Gould, Helen Huang, Guodong Long
Conference General Chairs, AJCAI 2025

 

Miaomiao Liu, Xin Yu
Conference Program Chairs, AJCAI 2025


Feng Liu, Jing Zhang, Yujiao Shi, Shunli Zhang
Conference Publicity Chairs, AJCAI 2025

 

----------

Dr. Jing Zhang

Lecturer

School of Computing

College of Systems & Society

The Australian National University (ANU)

Canberra, Australia

B161 Brian Anderson Building

W: https://comp.anu.edu.au/people/jing-zhang/

E: jing....@anu.edu.au

 

AJCAI2025.pdf
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