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ORCIDJournal of Artificial Intelligence Research, Volume 79
Volume 79, 2024
- Oskar van der Wal
, Dominik Bachmann, Alina Leidinger, Leendert van Maanen, Willem H. Zuidema, Katrin Schulz:
Undesirable Biases in NLP: Addressing Challenges of Measurement. 1-40 - Jérémie Sublime:
The AI Race: Why Current Neural Network-based Architectures are a Poor Basis for Artificial General Intelligence. 41-67 - Wolfgang Dvorák, Matthias König, Markus Ulbricht, Stefan Woltran:
Principles and their Computational Consequences for Argumentation Frameworks with Collective Attacks. 69-136 - Charlie Street, Bruno Lacerda, Manuel Mühlig, Nick Hawes:
Right Place, Right Time: Proactive Multi-Robot Task Allocation Under Spatiotemporal Uncertainty. 137-171 - Alessandro Suglia, Ioannis Konstas, Oliver Lemon:
Visually Grounded Language Learning: A Review of Language Games, Datasets, Tasks, and Models. 173-239 - Mohamed-Bachir Belaid, Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar, Helge Spieker:
Query-driven Qualitative Constraint Acquisition. 241-271 - Yang Cao, Ye Zhu, Kai Ming Ting, Flora D. Salim, Hong Xian Li, Luxing Yang, Gang Li:
Detecting Change Intervals with Isolation Distributional Kernel. 273-306 - Hans van Ditmarsch, Sunil Simon:
Boolean Observation Games. 307-357 - Carl Orge Retzlaff, Srijita Das, Christabel Wayllace, Payam Mousavi, Mohammad Afshari, Tianpei Yang, Anna Saranti, Alessa Angerschmid, Matthew E. Taylor, Andreas Holzinger:
Human-in-the-Loop Reinforcement Learning: A Survey and Position on Requirements, Challenges, and Opportunities. 359-415 - Giorgio Franceschelli, Mirco Musolesi:
Reinforcement Learning for Generative AI: State of the Art, Opportunities and Open Research Challenges. 417-446 - Ilario Bonacina, Maria Luisa Bonet, Jordi Levy:
Weighted, Circular and Semi-Algebraic Proofs. 447-482 - Stefano Ardizzoni, Irene Saccani, Luca Consolini, Marco Locatelli, Bernhard Nebel:
An Algorithm with Improved Complexity for Pebble Motion/Multi-Agent Path Finding on Trees. 483-514 - Mohit Kumar, Bernhard Alois Moser, Lukas Fischer:
On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach. 515-567 - Evan Yifan Xu, Pan Xu:
Exploring the Tradeoff Between System Profit and Income Equality Among Ride-hailing Drivers. 569-597 - Yixin Chen, Alan Kuhnle:
Practical and Parallelizable Algorithms for Non-Monotone Submodular Maximization with Size Constraint. 599-637 - Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter:
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML. 639-677 - Florian Felten, El-Ghazali Talbi, Grégoire Danoy:
Multi-Objective Reinforcement Learning Based on Decomposition: A Taxonomy and Framework. 679-723 - Daniele Meli, Alberto Castellini, Alessandro Farinelli:
Learning Logic Specifications for Policy Guidance in POMDPs: an Inductive Logic Programming Approach. 725-776 - Zari McFadden, Lauren Alvarez:
Performative Ethics From Within the Ivory Tower: How CS Practitioners Uphold Systems of Oppression. 777-799 - Alex Moore, Davide Morelli:
conDENSE: Conditional Density Estimation for Time Series Anomaly Detection. 801-824 - Xingwei Liang, Geng Tu, Jiachen Du, Ruifeng Xu:
Multi-Modal Attentive Prompt Learning for Few-shot Emotion Recognition in Conversations. 825-863 - Shaheen Fatima, Nicholas R. Jennings, Michael J. Wooldridge:
Learning to Resolve Social Dilemmas: A Survey. 895-969 - Yufan Wang, Zijing Wang, Kai Ming Ting, Yuanyi Shang:
A Principled Distributional Approach to Trajectory Similarity Measurement and its Application to Anomaly Detection. 865-893 - Uwe Peters, Mary Carman:
Cultural Bias in Explainable AI Research: A Systematic Analysis. 971-1000 - Anujit Chakraborty, Jatin Jindal, Swaprava Nath:
Removing Bias and Incentivizing Precision in Peer-grading. 1001-1046 - Alexandre Lemos, Filipe Gouveia, Pedro T. Monteiro, Inês Lynce:
Iterative Train Scheduling under Disruption with Maximum Satisfiability. 1047-1090 - Pingping Cao, Yanping Zhu, Yuhao Jin, Benkun Ruan, Qiang Niu:
DIGCN: A Dynamic Interaction Graph Convolutional Network Based on Learnable Proposals for Object Detection. 1091-1112 - Niclas Boehmer, Klaus Heeger, Stanislaw Szufa:
A Map of Diverse Synthetic Stable Matching Instances. 1113-1166 - Aditya Mohan, Amy Zhang, Marius Lindauer:
Structure in Deep Reinforcement Learning: A Survey and Open Problems. 1167-1236 - Xingrui Yu, Bo Han, Ivor W. Tsang:
USN: A Robust Imitation Learning Method against Diverse Action Noise. 1237-1280 - Arseniy Pertzovsky, Roie Zivan, Noa Agmon:
Collision Avoiding Max-Sum for Mobile Sensor Teams. 1281-1311 - Resmi RamachandranPillai, Md. Fahim Sikder, David Bergström, Fredrik Heintz:
Bt-GAN: Generating Fair Synthetic Healthdata via Bias-transforming Generative Adversarial Networks. 1313-1341
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