Dear all,
We are pleased to announce the Fourth Workshop on Computational Fair Division (CFD), co-located with the International Joint Conference on Artificial Intelligence (IJCAI) in Bremen, Germany, during August 15-21, 2026.
CFD Website: https://sites.google.com/view/fairdivisionworkshop2026/
Submission link: https://openreview.net/group?id=ijcai.org/IJCAI-ECAI/2026/Workshop/CFD
Important Dates — all dates are 11:59 pm, Anywhere on Earth (AoE):
Submission Deadline: May 9, 2026
Notification of Acceptance: June 8, 2026
One-day workshop: August 15-17, 2026
Papers should be submitted in IJCAI format, with a 7-page limit (excluding references).
There will be a 30-minute session for demonstrations of fair division applications.
Submission Deadline for the demonstration is May 22, 2026
The cutting-edge field of fair division has seen explosive growth in recent years, covering a wide range of important areas of interest. Recent advancements have paved the way for ground-breaking research in this area, answering important questions on how to allocate resources to agents with competing preferences while ensuring fairness, efficiency, constraint feasibility, and incentive-compatibility. Moreover, exploring the power and limitations of large language models, agentic AI, and other AI techniques for tackling complex fair allocation decisions has gained a significant amount of interest recently. This workshop brings together computational fairness researchers from all walks of life; theoretical, empirical, and applied; to discuss how to apply fair division to the challenges of modern society. We invite submissions that push the boundaries of the state-of-the-art in computational fair division on a variety of topics, including:
Classic fair allocation of indivisible items
Resource allocation problems (e.g., cake cutting, house allocation, matching, or apportionment)
Constrained fair division
Uncertainty & distortion in fair division
Fair division in social networks
Budget allocation
Market design
Competitive/market equilibria
Combinatorial auctions or optimization with fairness consideration
Perceived fairness; fairness in collective decision-making
Proportional representation
Apportionment methods
Fair representation
Fairness in cooperative game theory
Incentives in fair division
Automated theorem proving/SAT solving approaches for fair division
Empirical analysis of resource allocation problems
Datasets for and tools demonstrating practical implementation of fair division algorithms
ML approaches to fair division (e.g., learned preferences or on-line procedures)
Cooperative AI, Agentic AI, and LLM approaches to fair division
Applications of fair division approaches to other algorithmic fairness problems (e.g. ranking, fair LLMs, etc)
Task allocation in multi-robotic systems
Thank you,
CFD-2026 organizers (contact.c...@gmail.com)
Arpita Biswas, Eva Deltl, Hadi Hosseini, Joshua Kavner, Sanjukta Roy, Šimon Schierreich, and Yair Zick