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ICAPS 2025

A*

International Conference on Automated Planning and Scheduling

Official site ↗
53
accepted papers
49
authors
November 9-14, 2025
dates
Australia
location

53 / 53 papers

  1. 1
    A Flow Based Planning Method for Multi-Agent Progression with Deployable Agents and Communication Constraints
    Emile Siboulet
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  2. 2
    A Formalism for Optimal Search with Dynamic Heuristics
    Remo Christen
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  3. 3
    A Sampling Approach to Planning with Infinite Domain Control Variables
    Ángel Aso-Mollar
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  4. 4
    A* for Bounding Shortest Paths in the Graphs of Convex Sets
    Kaarthik Sundar
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  5. 5
    Agent Planning Programs as Non-deterministic Planning under Fairness
    Nitin Yadav
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  6. 6
    Alternation-Based Novelty Search
    Augusto B. Corrêa
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  7. 7
    An Improved Lower Bound on the Length of Locally-Improving Policy Sequences in MDPs with Large Action Sets
    Pratyush Agarwal
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  8. 8
    Analyzing Launch Operations Using the Spaceport Throughput Analysis Resource (STAR)
    Richard Levinson
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  9. 9
    Automating the Generation of Prompts for LLM-based Action Choice in PDDL Planning
    Katharina Stein
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  10. 10
    Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation
    Sukai Huang
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  11. 11
    Continuing the Quest for Polynomial Time Heuristics in PDDL Input Size: Tractable Cases for Lifted hᵃᵈᵈ
    Pascal Lauer
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  12. 12
    Cost-Optimal FOND Planning as Bi-Objective Best-First Search
    Diego Aineto
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  13. 13
    Delete-Free Planning with Object Creation is Undecidable
    Augusto B. Corrêa
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  14. 14
    DynTaskMAS: A Dynamic Task Graph-driven Framework for Asynchronous and Parallel LLM-based Multi-Agent Systems
    Junwei Yu
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  15. 15
    Frontmatter
    Daniel Harabor
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  16. 16
    Going Topological in Multi-risk Extended Markov Ratio Decision Processes
    Alexander Zadorojniy
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  17. 17
    Hardness of Chosen Length Planning Games and Regular Fixed Methods FOND HTN Planning
    Maurice Dekker
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  18. 18
    HDDLGym: A Tool for Studying Multi-Agent Hierarchical Problems Defined in HDDL with OpenAI Gym
    Ngoc La
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  19. 19
    How Good is Perfect? On the Incompleteness of A* for Total-Order HTN Planning
    Mohammad Yousefi
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  20. 20
    Howard's Policy Iteration is Subexponential for Deterministic Markov Decision Problems with Rewards of Fixed Bit-size and Arbitrary Discount Factor
    Dibyangshu Mukherjee
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  21. 21
    HTN Plan Repair Algorithms Compared: Strengths and Weaknesses of Different Methods
    Paul Zaidins
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  22. 22
    Initial Condition Retrieving for Hybrid and Numeric Planning Problems
    Matteo Cardellini
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  23. 23
    Instance-based Approximation Guarantees for Graph-based Nearest Neighbor Search
    Yannick Bosch
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  24. 24
    Is This Plan Necessarily Redundant? On the Computational Complexity of Unobserved Domain Learning
    Pascal Bachor
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  25. 25
    Knowledge Engineering for Planning and Scheduling in the LLM Era
    Mauro Vallati
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  26. 26
    Landmark Generation in HTN Planning Revisited
    Victor Scherer Putrich
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  27. 27
    Learning Efficiency Meets Symmetry Breaking
    Yingbin Bai
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  28. 28
    Learning Lifted STRIPS Models from Action Traces alone: A Simple, General, and Scalable Solution
    Jonas Gösgens
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  29. 29
    Leveraging Action Relational Structures for Integrated Learning and Planning
    Ryan Xiao Wang
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  30. 30
    LTLf Adaptive Synthesis for Multi-Tier Goals in Nondeterministic Domains
    Giuseppe De Giacomo
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  31. 31
    New Exact Methods for Solving Quadratic Traveling Salesman Problem
    Yuxiao Chen
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  32. 32
    Observation Adaptation via Annealed Importance Resampling for Partially Observable Markov Decision Processes
    Yunuo Zhang
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  33. 33
    On Generating Robust Plans and Linear Execution Strategies in Planning Against Nature
    Lukás Chrpa
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  34. 34
    On Picking Good Policies: Leveraging Action-Policy Testing in Policy Training
    Jan Eisenhut
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  35. 35
    On Planning Through LLMs
    Mattia Chiari
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  36. 36
    On the Gains from Using Action Observations in Domain Repair
    Alba Gragera
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  37. 37
    On the Notion of Plan Quality for PDDL+
    Francesco Percassi
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  38. 38
    On Using Lazy Greedy Best-First Search with Subgoaling Relaxation in Numeric Planning Problems
    Enrico Scala
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  39. 39
    Parallelizing Multi-objective A* Search
    Saman Ahmadi
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  40. 40
    Partially Observable Monte-Carlo Graph Search
    Yang You
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  41. 41
    Per-Domain Generalizing Policies: On Validation Instances and Scaling Behavior
    Timo P. Gros
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  42. 42
    Platform-Aware Mission Planning
    Stefan Panjkovic
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  43. 43
    Posthoc: The Visualisation Platform for Search
    Kevin Zheng
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  44. 44
    Potential Heuristics: Weakening Consistency Constraints
    Pascal Lauer
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  45. 45
    Proceedings of the Thirty-Fifth International Conference on Automated Planning and Scheduling, ICAPS 2025, Melbourne, Victoria, Australia, November 9-14, 2025
    Daniel Harabor
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  46. 46
    Pseudo-Boolean Proof Logging for Optimal Classical Planning
    Simon Dold
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  47. 47
    Quality Diversity for Variational Quantum Circuit Optimization
    Maximilian Zorn
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  48. 48
    Rack Position Optimization in Large-Scale Heterogeneous Data Centers
    Chang-Lin Chen
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  49. 49
    Revisiting LLMs in Planning from Literature Review: a Semi-Automated Analysis Approach and Evolving Categories Representing Shifting Perspectives
    Vishal Pallagani
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  50. 50
    Safe Interval Randomized Path Planning For Manipulators
    Nuraddin Kerimov
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