Programs

ICAPS 2026 Keynotes Tuesday, June 30 Nick Hawes Better Autonomy Through Uncertainty Real robots perceive imperfectly, act unreliably, and rarely have an accurate model of the world they're operating in. Therefore any long-running, goal-directed robot mission has to treat uncertainty as a first-class concern rather than an afterthought. For over a decade we've approached this through an explicitly model-based, decision-theoretic planning framework that integrates learning and supports a range of specification types.

Quick Navigation Sunday 28/06 Monday 29/06 Tuesday 30/06 Wednesday 01/07 Thursday 02/07 × Lunch at ICAPS 2026 Lunch is provided to all participants from June 28th to July 2nd (inclusive). On June 27th, lunch is provided to DC & Launchpad participants (students, mentors, organizers) and to the Council participants. June 27th, 28th, 29th: Chef's Selection of Sandwiches, Soup, Tea & Coffee June 30th, July 1st, 2nd: Buffet Lunch (1 Main Course & 1 Vegan Main Course) served with Seasonal Vegetables, Rice & Potatoes, and Tea & Coffee Sunday, June 28, 2026 — Workshops & Tutorials Day 1 ↑ Back to Navigation 09:00 – 12:30 — Morning Sessions (Coffee Break 10:30 – 10:50 in the open space and meeting rooms on the second floor) GenPlan Generalization in Planning — Full Day — Room 6 HAXP Human-Aware and Explainable Planning — Full Day — Room 3 KEPS Knowledge Engineering for Planning and Scheduling — Full Day — Room 9 PRL Bridging the Gap Between AI Planning and (Reinforcement) Learning — Full Day — Room 1+2 Tutorial 1: Language2Plan Language-to-Plan — Room 5 Tutorial 2: Deepxube A Hands-on Deepxube Tutorial — Room 7 13:00 – 14:30 — Lunch — Sussex Restaurant 14:30 – 18:00 — Afternoon Sessions (Coffee Break 16:00 – 16:20 in the open space and meeting rooms on the second floor) GenPlan Generalization in Planning — Full Day — Room 6 HAXP Human-Aware and Explainable Planning — Full Day — Room 3 KEPS Knowledge Engineering for Planning and Scheduling — Full Day — Room 9 PRL Bridging the Gap Between AI Planning and (Reinforcement) Learning — Full Day — Room 1+2 RPG Roles of Planning in Games — Room 5 PR-BGI Planning and Reasoning about Beliefs, Goals and Intentions — Room 7 Monday, June 29, 2026 — Workshops & Tutorials Day 2 ↑ Back to Navigation 09:00 – 12:30 — Morning Sessions (Coffee Break 10:30 – 10:50 in the open space and meeting rooms on the second floor) LM4Plan Planning in the Era of Large Language Models — Full Day — Room 1+2 PlanRob Planning and Robotics — Full Day — Room 9 HSDIP Heuristics and Search for Domain-independent Planning — Full Day — Room 7 RIPL Reliability in Planning and Learning — Full Day — Room 6 Tutorial 3: Planning Ontology Planning Ontology — Room 5 12:30 – 14:00 — Lunch — Sussex Restaurant 14:00 – 17:30 — Afternoon Sessions (Coffee Break 15:30 – 15:50 in the open space and meeting rooms on the second floor) LM4Plan Planning in the Era of Large Language Models — Full Day — Room 1+2 PlanRob Planning and Robotics — Full Day — Room 9 HSDIP Heuristics and Search for Domain-independent Planning — Full Day — Room 7 RIPL Reliability in Planning and Learning — Full Day — Room 6 CASP:ER Constraint and Satisfiability-based Planning — Room 3 HPlan Hierarchical Planning — Room 5 Opening Reception (17:30 – 19:30) — Fitzwilliam Suites & Pre-Function Area Tuesday, June 30, 2026 — Main Conference Day 1 ↑ Back to Navigation 08:45 – 09:00 — Opening Remarks — Plenary Room - Pembroke & Herbert 09:00 – 10:00 — Invited Talk: Nick Hawes — Plenary Room - Pembroke & Herbert 10:00 – 10:30 — Coffee Break — Fitzwilliam Suites & Pre-Function Area 10:30 – 12:00 — Morning Sessions Session 1A: Classical Planning I Plenary Room - Pembroke & Herbert — Chair: Gabriele Röger 10:30   Simplifying Planning Tasks with Fact-Level Relevance Analysis Cameron Allen, Anita de Mello Koch, Harsha Kokel, George Konidaris and Michael Katz 10:45   Monotonic Variants of Saturated Cost Partitioning Mauricio Salerno, Raquel Fuentetaja and Jendrik Seipp 10:55   Potential Heuristics as Real-Valued Multilinear Polynomials Best Paper Runner-Up Augusto B.

Workshop on Heuristics and Search for Domain-independent Planning (HSDIP 2026) Important dates Schedule Submission May 7, 2026 May 14, 2026 Notification May 28, 2026 Camera Ready June 8, 2026 June 14, 2026 Workshop June 29, 2026 All deadlines are AoE(UTC-12). Aim and Scope of the Workshop Heuristics and search algorithms are the two key components of heuristic search, one of the main approaches to many variations of domain-independent planning, including classical planning, temporal planning, planning under uncertainty and adversarial planning.

HAXP: Human-Aware and Explainable Planning ICAPS 2026 Workshop Dublin, Ireland June 28, 2026 Program Time Session 9:00–9:15 Welcome & Opening Remarks 9:15–10:15 Keynote 1: Explainable Reasoning and Learning in Ad hoc Teamwork Mohan Sridharan 10:30–10:50 Coffee Break 10:50–12:30 Paper Session 1 Generalized Execution for Dialogue Planning — Victoria Armstrong, Christian Muise Iterative Planning with MUGS Explanations: Exploring the Design Space — Johannes Schmalz, David Groß, Rebecca Eifler, Julián Méndez, Raimund Dachselt, Stefan Gumhold, Jörg Hoffmann

List of Papers Accepted to ICAPS 2026 Previously Published Papers Papers accepted to the Main Tracks I Always Told My Mom That Order Is Overrated: Unordered HTN Planning is in PSPACE and Models Problems Beyond STRIPS Pascal Lauer, Yifan Zhang, Patrik Haslum and Pascal Bercher db-LaCAM: Fast and Scalable Multi-Robot Kinodynamic Motion Planning with Discontinuity-Bounded Search and Lightweight MAPF Akmaral Moldagalieva, Keisuke Okumura, Amanda Prorok and Wolfgang Hoenig Polynomial-time Configuration Generator for Connected Unlabeled Multi-Agent Pathfinding Takahiro Suzuki and Keisuke Okumura Rating Composite AI Models for Robustness Through Probabilistic Planning Kausik Lakkaraju, Sunandita Patra, Parisa Zehtabi and Biplav Srivastava LaCAM* Variants for Minimizing Makespan in Multi-Agent Path Finding Omer Idgar, Dor Atzmon and Ariel Felner Complete and Optimal Robust Planning against Nature Lukas Chrpa and Erez Karpas Relaxing is Hard: Complexity Results for Lifted Partial Order Causal Link Planning Harrison Oates and Pascal Bercher Domain-Independent Dynamic Programming with Constraint Propagation Imko Marijnissen, Christopher Beck, Emir Demirović and Ryo Kuroiwa AUPO - Abstracted until proven otherwise: A reward distribution based abstraction algorithm Robin Schmöcker, Alexander Dockhorn and Bodo Rosenhahn Beyond Hard Constraints: Budget-Conditioned Reachability For Safe Offline Reinforcement Learning Janaka Brahmanage and Akshat Kumar Robust Crop Planning under Uncertainty: Aligning Economic Optimality with Agronomic Sustainability Runhao Liu, Ziming Chen, You Li and Peng Zhang Algorithms for Deciding the Safety of States in Fully Observable Non-deterministic Problems Johannes Schmalz and Chaahat Jain Sample-Efficient Hypergradient Estimation for Decentralized Bi-Level Reinforcement Learning Mikoto Kudo, Takumi Tanabe, Akifumi Wachi and Youhei Akimoto Complexity Results for Fixing Classical Models Using LTL to Express Which Solutions Are (Un)Desired Huanghua Sheng and Pascal Bercher Domain Model Acquisition From Binary Traces Arash Haratian, Arnaud Lequen, Daniel Gnad and Jendrik Seipp Self-Improvement for Fast, High-Quality Plan Generation Robert Gieselmann, Henrike von Huelsen, Mihai Samson, Marie-Christine Meyer, Dariusz Piotrowski, Oleksandr Radomskyi, Justin Okamoto, Turan Gojayev, Michael Painter, Gavin Brown, Federico Pecora and Jeremy Wyatt Simplifying Planning Tasks with Fact-Level Relevance Analysis Cameron Allen, Anita de Mello Koch, Harsha Kokel, George Konidaris and Michael Katz Deep RL for Fast Long-Horizon Operations Scheduling on NASA’s Carruthers Geocorona Observatory Mission Alex Zhang, Jackson Craig and Lara Waldrop Planning in the LLM Era: Building for Reliability and Efficiency Michael Katz, Harsha Kokel, Kavitha Srinivas and Shirin Sohrabi Automating Thought of Search: A Journey Towards Soundness and Completeness Daniel Cao, Michael Katz, Harsha Kokel, Kavitha Srinivas and Shirin Sohrabi Risk-Bounded Multi-Agent Visual Navigation via Iterative Risk Allocation Viraj Parimi and Brian Williams Dynamic Shelf Arrangement and Task Assignment with Stable Matching for Multi-Agent Pickup and Delivery with Multi-Item Packing Problem Yosuke Fujisawa, Yusaku Wakasugi, Kazuya Nakazawa, Ryo Matsubara and Toshiharu Sugawara QSIM: Mitigating Overestimation in Multi-Agent Reinforcement Learning via Action Similarity Weighted Q-Learning Yuanjun Li, Bin Zhang, Hao Chen, Zhouyang Jiang, Dapeng Li and Zhiwei Xu Beyond Message Passing: Modern GNN Architectures for Online Planner Selection Jana Vatter, Ruben Mayer, Hans-Arno Jacobsen, Horst Samulowitz and Michael Katz Planning as Goal Recognition: Deriving Heuristics from Intention Models Giacomo Rosa, Jean Honorio, Nir Lipovetzky and Sebastian Sardina H-ANTS: Hierarchical Ant System with Insert-and-Prune Charging for Capacitated Electric Vehicle Routing Chuyin Peng, Feng-Feng Wei and Wei-Neng Chen Incremental LTLf Synthesis Giuseppe De Giacomo, Yves Lespérance, Gianmarco Parretti, Fabio Patrizi and Moshe Y.

14th Workshop on Planning and Robotics (PlanRob) Co-located workshop at ICAPS'26 Dublin, Ireland June 29, 2026 Paper submission deadline extended to 2nd of May, 2026. Aim and Scope of the Workshop AI Planning & Scheduling (P&S) methods are crucial to enabling intelligent robots to perform autonomous, flexible, and interactive behaviors, but they must be tightly integrated into the overall robot architecture in order to be effective. This requires strong collaboration between researchers from both the AI and the Robotics communities.

Workshop on Generalization in Planning (GenPlan) ICAPS 2026 Workshop Dublin, Ireland, June 28, 2026 Official Website: https://aair-lab.github.io/genplan26 Aim and Scope of the Workshop Generalization and transfer are essential components of intelligence, and significant research efforts have been dedicated to addressing these challenges in sequential decision-making. However, this research is often fragmented across largely parallel research communities such as AI planning, reinforcement learning, model learning, robotics, etc. Recent advances in deep reinforcement learning and generative AI have led to data-driven methods that are effective for short-horizon reasoning and decision-making, with open problems regarding sample efficiency, guarantees of correctness, and applicability to long-horizon settings.

Workshop on Hierarchical Planning (HPlan) Please see here for more details.

Workshop on Knowledge Engineering for Planning and Scheduling (KEPS) 2026 Workshop on Knowledge Engineering for Planning and Scheduling Dublin, Ireland KEPS 2026 website Important Dates Call for Papers announcement: March 17th, 2026 Paper submission deadline: April 16th, 2026 Notification of Acceptance: May 20th, 2026 Aim and Scope of the Workshop Despite the progress in automated planning and scheduling systems, these systems still need to be fed by carefully engineered domain and problem descriptions and they need to be fine-tuned for particular domains and problems.

Constraint And Satisfiability-based Planning: an Exploratory Research Workshop (CASP:ER 2026) Despite the widespread adoption of heuristic search and learning-based approaches in automated planning, Constraint and Satisfiability-based Planning (CSP/SAT-based Planning) remains a viable and promising paradigm. Historically, CSP and SAT approaches have demonstrated strong theoretical foundations and practical success in various domains. However, their usage has diminished in recent years due to the rise of alternative methods. The CASP:ER workshop aims to revisit and reinforce the relevance of CSP/SAT-based planning by showcasing recent advancements, discussing its applicability, and identifying opportunities for renewed adoption.