| 2025 | Parallelizing Multi-objective A* Search. | Saman Ahmadi, Nathan R. Sturtevant, Andrea Raith, Daniel Harabor, Mahdi Jalili |
| 2025 | An Improved Lower Bound on the Length of Locally-Improving Policy Sequences in MDPs with Large Action Sets. | Pratyush Agarwal, Mulinti Shaik Wajid, Shivaram Kalyanakrishnan |
| 2024 | Decentralized, Decomposition-Based Observation Scheduling for a Large-Scale Satellite Constellation. | Itai Zilberstein, Ananya Rao, Matthew Salis, Steve A. Chien |
| 2024 | Improving the Efficiency and Efficacy of Multi-Agent Reinforcement Learning on Complex Railway Networks with a Local-Critic Approach. | Yuan Zhang, Umashankar Deekshith, Jianhong Wang, Joschka Boedecker |
| 2024 | Planning and Execution in Multi-Agent Path Finding: Models and Algorithms. | Yue Zhang, Zhe Chen, Daniel Harabor, Pierre Le Bodic, Peter J. Stuckey |
| 2024 | Contrastive Explanations of Centralized Multi-agent Optimization Solutions. | Parisa Zehtabi, Alberto Pozanco, Ayala Bolch, Daniel Borrajo, Sarit Kraus |
| 2024 | Control in Stochastic Environment with Delays: A Model-based Reinforcement Learning Approach. | Zhiyuan Yao, Ionut Florescu, Chihoon Lee |
| 2024 | Neuro-Symbolic Learning of Lifted Action Models from Visual Traces. | Kai Xi, Stephen Gould, Sylvie Thibaux |
| 2024 | MAPF in 3D Warehouses: Dataset and Analysis. | Qian Wang, Rishi Veerapaneni, Yu Wu, Jiaoyang Li, Maxim Likhachev |
| 2024 | Learning Generalised Policies for Numeric Planning. | Ryan Xiao Wang, Sylvie Thibaux |
| 2024 | Efficient Approximate Search for Multi-Objective Multi-Agent Path Finding. | Fangji Wang, Han Zhang, Sven Koenig, Jiaoyang Li |
| 2024 | Neural Action Policy Safety Verification: Applicablity Filtering. | Marcel Vinzent, Jrg Hoffmann |
| 2024 | Improving Learnt Local MAPF Policies with Heuristic Search. | Rishi Veerapaneni, Qian Wang, Kevin Ren, Arthur Jakobsson, Jiaoyang Li, Maxim Likhachev |
| 2024 | Optimal Infinite Temporal Planning: Cyclic Plans for Priced Timed Automata. | Rasmus G. Tollund, Nicklas S. Johansen, Kristian . Nielsen, lvaro Torralba, Kim G. Larsen |
| 2024 | Multi-Agent Temporal Task Solving and Plan Optimization. | J. Caballero Testn, Mara D. R.-Moreno |
| 2024 | Robust Multi-Agent Pathfinding with Continuous Time. | Wen Jun Tan, Xueyan Tang, Wentong Cai |
| 2024 | Multi-Robot Connected Fermat Spiral Coverage. | Jingtao Tang, Hang Ma |
| 2024 | Addressing Myopic Constrained POMDP Planning with Recursive Dual Ascent. | Paula Stocco, Suhas Chundi, Arec L. Jamgochian, Mykel J. Kochenderfer |
| 2024 | Explaining the Space of SSP Policies via Policy-Property Dependencies: Complexity, Algorithms, and Relation to Multi-Objective Planning. | Marcel Steinmetz, Sylvie Thibaux, Daniel Hller, Florent Teichteil-Knigsbuch |
| 2024 | Merging or Computing Saturated Cost Partitionings? A Merge Strategy for the Merge-and-Shrink Framework. | Silvan Sievers, Thomas Keller, Gabriele Rger |
| 2024 | Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents. | Yash Shukla, Tanushree Burman, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov |
| 2024 | Imitating Cost-Constrained Behaviors in Reinforcement Learning. | Qian Shao, Pradeep Varakantham, Shih-Fen Cheng |
| 2024 | Accelerating Search-Based Planning for Multi-Robot Manipulation by Leveraging Online-Generated Experiences. | Yorai Shaoul, Itamar Mishani, Maxim Likhachev, Jiaoyang Li |
| 2024 | Efficiently Computing Transitions in Cartesian Abstractions. | Jendrik Seipp |
| 2024 | Learning General Policies for Planning through GPT Models. | Nicholas Rossetti, Massimiliano Tummolo, Alfonso Emilio Gerevini, Luca Putelli, Ivan Serina, Mattia Chiari, Matteo Olivato |