| 2024 | A Counter-Example Based Approach to Probabilistic Conformant Planning. Xiaodi Zhang, Alban Grastien, Charles Gretton |
| 2024 | A Fast Algorithm for k-Memory Messaging Scheme Design in Dynamic Environments with Uncertainty. Zhikang Fan, Weiran Shen |
| 2024 | A Real-Time Rescheduling Algorithm for Multi-robot Plan Execution. Ying Feng, Adittyo Paul, Zhe Chen, Jiaoyang Li |
| 2024 | Abstraction Heuristics for Factored Tasks. Clemens Büchner, Patrick Ferber, Jendrik Seipp, Malte Helmert |
| 2024 | Accelerating Search-Based Planning for Multi-Robot Manipulation by Leveraging Online-Generated Experiences. Yorai Shaoul, Itamar Mishani, Maxim Likhachev, Jiaoyang Li |
| 2024 | Action Model Learning from Noisy Traces: a Probabilistic Approach. Leonardo Lamanna, Luciano Serafini |
| 2024 | Addressing Myopic Constrained POMDP Planning with Recursive Dual Ascent. Paula Stocco, Suhas Chundi, Arec L. Jamgochian, Mykel J. Kochenderfer |
| 2024 | An Analysis of the Decidability and Complexity of Numeric Additive Planning. Hayyan Helal, Gerhard Lakemeyer |
| 2024 | Bounded-Suboptimal Weight-Constrained Shortest-Path Search via Efficient Representation of Paths. Han Zhang, Oren Salzman, Ariel Felner, T. K. Satish Kumar, Sven Koenig |
| 2024 | Combined Task and Motion Planning via Sketch Decompositions. Magí Dalmau-Moreno, Néstor García, Vicenç Gómez, Hector Geffner |
| 2024 | Computing Planning Centroids and Minimum Covering States Using Symbolic Bidirectional Search. Alberto Pozanco, Álvaro Torralba, Daniel Borrajo |
| 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 | Converting Simple Temporal Networks with Uncertainty into Minimal Equivalent Dispatchable Form. Luke Hunsberger, Roberto Posenato |
| 2024 | Decentralized, Decomposition-Based Observation Scheduling for a Large-Scale Satellite Constellation. Itai Zilberstein, Ananya Rao, Matthew Salis, Steve A. Chien |
| 2024 | Decoupled Search for the Masses: A Novel Task Transformation for Classical Planning. David Speck, Daniel Gnad |
| 2024 | Efficient Approximate Search for Multi-Objective Multi-Agent Path Finding. Fangji Wang, Han Zhang, Sven Koenig, Jiaoyang Li |
| 2024 | Efficiently Computing Transitions in Cartesian Abstractions. Jendrik Seipp |
| 2024 | Epistemic Exploration for Generalizable Planning and Learning in Non-Stationary Settings. Rushang Karia, Pulkit Verma, Alberto Speranzon, Siddharth Srivastava |
| 2024 | Exact Multi-objective Path Finding with Negative Weights. Saman Ahmadi, Nathan R. Sturtevant, Daniel Harabor, Mahdi Jalili |
| 2024 | Explaining Plan Quality Differences. Benjamin Krarup, Amanda Jane Coles, Derek Long, David E. Smith |
| 2024 | Explaining the Space of SSP Policies via Policy-Property Dependencies: Complexity, Algorithms, and Relation to Multi-Objective Planning. Marcel Steinmetz, Sylvie Thiébaux, Daniel Höller, Florent Teichteil-Königsbuch |
| 2024 | Expressiveness of Graph Neural Networks in Planning Domains. Rostislav Horcík, Gustav Sír |
| 2024 | Formal Representations of Classical Planning Domains. Claudia Grundke, Gabriele Röger, Malte Helmert |
| 2024 | Higher-Dimensional Potential Heuristics: Lower Bound Criterion and Connection to Correlation Complexity. Simon Dold, Malte Helmert |
| 2024 | Imitating Cost-Constrained Behaviors in Reinforcement Learning. Qian Shao, Pradeep Varakantham, Shih-Fen Cheng |
| 2024 | Improving Learnt Local MAPF Policies with Heuristic Search. Rishi Veerapaneni, Qian Wang, Kevin Ren, Arthur Jakobsson, Jiaoyang Li, Maxim Likhachev |
| 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 | Incremental Ordering for Scheduling Problems. Stefan Neubert, Katrin Casel |
| 2024 | Investigating Large Neighbourhood Search for Bus Driver Scheduling. Tommaso Mannelli Mazzoli, Lucas Kletzander, Pascal Van Hentenryck, Nysret Musliu |
| 2024 | JaxPlan and GurobiPlan: Optimization Baselines for Replanning in Discrete and Mixed Discrete-Continuous Probabilistic Domains. Michael Gimelfarb, Ayal Taitler, Scott Sanner |
| 2024 | Large Language Models as Planning Domain Generators. James T. Oswald, Kavitha Srinivas, Harsha Kokel, Junkyu Lee, Michael Katz, Shirin Sohrabi |
| 2024 | Learning General Policies for Planning through GPT Models. Nicholas Rossetti, Massimiliano Tummolo, Alfonso Emilio Gerevini, Luca Putelli, Ivan Serina, Mattia Chiari, Matteo Olivato |
| 2024 | Learning Generalised Policies for Numeric Planning. Ryan Xiao Wang, Sylvie Thiébaux |
| 2024 | Learning Quadruped Locomotion Policies Using Logical Rules. David DeFazio, Yohei Hayamizu, Shiqi Zhang |
| 2024 | Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents. Yash Shukla, Tanushree Burman, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov |
| 2024 | Lookahead Pathology in Monte-Carlo Tree Search. Khoi P. N. Nguyen, Raghuram Ramanujan |
| 2024 | MAPF in 3D Warehouses: Dataset and Analysis. Qian Wang, Rishi Veerapaneni, Yu Wu, Jiaoyang Li, Maxim Likhachev |
| 2024 | Map Connectivity and Empirical Hardness of Grid-based Multi-Agent Pathfinding Problem. Jingyao Ren, Eric Ewing, T. K. Satish Kumar, Sven Koenig, Nora Ayanian |
| 2024 | Merging or Computing Saturated Cost Partitionings? A Merge Strategy for the Merge-and-Shrink Framework. Silvan Sievers, Thomas Keller, Gabriele Röger |
| 2024 | More Flexible Proximity Wildcards Path Planning with Compressed Path Databases. Xi Chen, Yue Zhang, Yonggang Zhang |
| 2024 | Multi-Agent Temporal Task Solving and Plan Optimization. J. Caballero Testón, María D. R.-Moreno |
| 2024 | Multi-Objective Electric Vehicle Route and Charging Planning with Contraction Hierarchies. Marek Cuchý, Jirí Vokrínek, Michal Jakob |
| 2024 | Multi-Robot Connected Fermat Spiral Coverage. Jingtao Tang, Hang Ma |
| 2024 | Neural Action Policy Safety Verification: Applicablity Filtering. Marcel Vinzent, Jörg Hoffmann |
| 2024 | Neural Combinatorial Optimization on Heterogeneous Graphs: An Application to the Picker Routing Problem in Mixed-shelves Warehouses. Laurin Luttmann, Lin Xie |
| 2024 | Neuro-Symbolic Learning of Lifted Action Models from Visual Traces. Kai Xi, Stephen Gould, Sylvie Thiébaux |
| 2024 | New Fuzzing Biases for Action Policy Testing. Jan Eisenhut, Xandra Schuler, Daniel Fiser, Daniel Höller, Maria Christakis, Jörg Hoffmann |
| 2024 | Non-deterministic Planning for Hyperproperty Verification. Raven Beutner, Bernd Finkbeiner |
| 2024 | On Policy Reuse: An Expressive Language for Representing and Executing General Policies that Call Other Policies. Blai Bonet, Dominik Drexler, Hector Geffner |
| 2024 | On Verifying Linear Execution Strategies in Planning Against Nature. Lukás Chrpa, Erez Karpas |
| 2024 | On the Computational Complexity of Stackelberg Planning and Meta-Operator Verification. Gregor Behnke, Marcel Steinmetz |
| 2024 | On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS). Vishal Pallagani, Bharath C. Muppasani, Kaushik Roy, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh, Amit P. Sheth |
| 2024 | Online Control of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning. Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh |
| 2024 | Optimal Infinite Temporal Planning: Cyclic Plans for Priced Timed Automata. Rasmus G. Tollund, Nicklas S. Johansen, Kristian Ø. Nielsen, Álvaro Torralba, Kim G. Larsen |
| 2024 | PDDL+ Models for Deployable yet Effective Traffic Signal Optimisation. Anas El Kouaiti, Francesco Percassi, Alessandro Saetti, Thomas Leo McCluskey, Mauro Vallati |
| 2024 | Planning Domain Simulation: An Interactive System for Plan Visualisation. Emanuele De Pellegrin, Ronald P. A. Petrick |
| 2024 | Planning and Acting While the Clock Ticks. Andrew Coles, Erez Karpas, Andrey Lavrinenko, Wheeler Ruml, Solomon Eyal Shimony, Shahaf S. Shperberg |
| 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 | Planning with Object Creation. Augusto B. Corrêa, Giuseppe De Giacomo, Malte Helmert, Sasha Rubin |
| 2024 | Planning with a Learned Policy Basis to Optimally Solve Complex Tasks. David Kuric, Guillermo Infante, Vicenç Gómez, Anders Jonsson, Herke van Hoof |
| 2024 | Preference Explanation and Decision Support for Multi-Objective Real-World Test Laboratory Scheduling. Florian Mischek, Nysret Musliu |
| 2024 | Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, ICAPS 2024, Banff, Alberta, Canada, June 1-6, 2024. Sara Bernardini, Christian Muise |
| 2024 | Progressive State Space Disaggregation for Infinite Horizon Dynamic Programming. Orso Forghieri, Hind Castel, Emmanuel Hyon, Erwan Le Pennec |
| 2024 | Replanning in Advance for Instant Delay Recovery in Multi-Agent Applications: Rerouting Trains in a Railway Hub. Issa K. Hanou, Devin Wild Thomas, Wheeler Ruml, Mathijs de Weerdt |
| 2024 | Rethinking Mutual Information for Language Conditioned Skill Discovery on Imitation Learning. Zhaoxun Ju, Chao Yang, Fuchun Sun, Hongbo Wang, Yu Qiao |
| 2024 | Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning. Dillon Z. Chen, Felipe W. Trevizan, Sylvie Thiébaux |
| 2024 | Robust Multi-Agent Pathfinding with Continuous Time. Wen Jun Tan, Xueyan Tang, Wentong Cai |
| 2024 | SKATE : Successive Rank-based Task Assignment for Proactive Online Planning. Déborah Conforto Nedelmann, Jérôme Lacan, Caroline P. C. Chanel |
| 2024 | SLAMuZero: Plan and Learn to Map for Joint SLAM and Navigation. Bowen Fang, Xu Chen, Zhengkun Pan, Xuan Di |
| 2024 | Safe Explicable Planning. Akkamahadevi Hanni, Andrew Boateng, Yu Zhang |
| 2024 | Safe Learning of PDDL Domains with Conditional Effects. Argaman Mordoch, Enrico Scala, Roni Stern, Brendan Juba |
| 2024 | SayNav: Grounding Large Language Models for Dynamic Planning to Navigation in New Environments. Abhinav Rajvanshi, Karan Sikka, Xiao Lin, Bhoram Lee, Han-Pang Chiu, Alvaro Velasquez |
| 2024 | Specifying Goals to Deep Neural Networks with Answer Set Programming. Forest Agostinelli, Rojina Panta, Vedant Khandelwal |
| 2024 | Taming Discretised PDDL+ through Multiple Discretisations. Matteo Cardellini, Marco Maratea, Francesco Percassi, Enrico Scala, Mauro Vallati |
| 2024 | Termination Properties of Transition Rules for Indirect Effects. Mojtaba Elahi, Saurabh Fadnis, Jussi Rintanen |
| 2024 | The Story So Far on Narrative Planning. Rogelio E. Cardona-Rivera, Arnav Jhala, Julie Porteous, R. Michael Young |
| 2024 | Tightest Admissible Shortest Path. Eyal Weiss, Ariel Felner, Gal A. Kaminka |
| 2024 | Towards Feasible Higher-Dimensional Potential Heuristics. Daniel Fiser, Marcel Steinmetz |
| 2024 | Transition Landmarks from Abstraction Cuts. Florian Pommerening, Clemens Büchner, Thomas Keller |
| 2024 | Unifying and Certifying Top-Quality Planning. Michael Katz, Junkyu Lee, Shirin Sohrabi |
| 2024 | Versatile Cost Partitioning with Exact Sensitivity Analysis. Paul Höft, David Speck, Florian Pommerening, Jendrik Seipp |
| 2024 | Weak and Strong Reversibility of Non-deterministic Actions: Universality and Uniformity. Jakub Med, Lukás Chrpa, Michael Morak, Wolfgang Faber |