CFP: Computational Fair Division Workshop @ IJCAI

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 4, 2026
Notification of Acceptance: June 6, 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

 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  ([email protected])
Arpita Biswas, Eva Deltl, Hadi Hosseini, Joshua Kavner, Sanjukta Roy, Šimon
Schierreich, and Yair Zick

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