The Journal of Artificial Intelligence Research (JAIR) is dedicated to the rapid dissemination of important research results to the global artificial intelligence (AI) community. The journal’s scope encompasses all areas of AI, including agents and multi-agent systems, automated reasoning, constraint processing and search, knowledge representation, machine learning, natural language, planning and scheduling, robotics and vision, and uncertainty in AI.

Vol. 86 (2026)

Published: 2026-05-15

Explainable Bayesian Deep Learning through Input-skip Latent Binary Bayesian Neural Networks

Eirik HÃļyheim, Lars Skaaret-Lund, Solve SÃĶbÃļ, Aliaksandr Hubin

Maximizing the Spread of Influence through a Social Network Using Partial Incentives

Abhishek K. Umrawal, Eliot W. Robson, Vaneet Aggarwal, Christopher J. Quinn

Doing More with Less: A Survey on Routing Strategies for Resource Optimisation in Large Language Model-Based Systems

Clovis Varangot-Reille, Christophe Bouvard, Mathieu Ciancone, Antoine Gourru, Marion Schaeffer, François Jacquenet

Language Model Self-improvement by Reinforcement Learning Contemplation without External Supervision

Jing-Cheng Pang, Kaiyuan Li, Pengyuan Wang, Xiong-Hui Chen, Jiacheng Xu, Zongzhang Zhang, Yang Yu

Trustworthy AI and Mixed Reality in Police Interventions: Challenges and Opportunities

Andreas BrÃĪnnstrÃķm, Eduardo García Laredo, Bernat Vivolas Jorda, Lola Valles, Jonas Hansson, Emili Martinez CaÃąaveras, Anders Schogster, David Martin-Moncunill, Juan Carlos Nieves

It’s About Time: Temporal References in Emergent Communication

Olaf Lipinski, Adam J. Sobey, Federico Cerutti, Timothy J. Norman

Adapting the Conflict-Based Search Framework for the Virtual Network Embedding Problem

Yi Zheng, Erik Kline, Lincoln Thurlow, Srivatsan Ravi, Sven Koenig, T. K. Satish Kumar

Causal Explanations for Image Classifiers

Hana Chockler, David A. Kelly, Daniel Kroening, Youcheng Sun

Explaining Multivariate Decision Trees: Characterising Tractable Languages

ClÃĐment Carbonnel, Martin C. Cooper, Emmanuel HÃĐbrard, Dany Morales, JoÃĢo Marques-Silva

Safe Learning of Multi-Agent Action Models from Concurrent Joint Action Observations

Argaman Mordoch, Ori Karat, Lea Shmilovich, Yarin Benyamin, Brendan Juba, Roni Stern
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