List of Papers Accepted to ICAPS 2025

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Applications

Revisiting LLMs in Planning from Literature Review: a Semi-Automated Analysis Approach and Evolving Categories Representing Shifting Perspectives 🔗

Vishal Pallagani, Nitin Gupta, Bharath Chandra Muppasani, Biplav Srivastava

Keywords: PS: Applications

Rack Position Optimization in Large-Scale Heterogeneous Data Centers 🔗

Chang-Lin Chen, Jiayu Chen, Tian Lan, Zhaoxia Zhao, Hongbo Dong, Vaneet Aggarwal

Keywords: PS: Applications, PS: Learning for planning and scheduling

A Flow Based Planning Method for Multi-Agent Progression with Deployable Agents and Communication Constraints 🔗

Emile Siboulet, Roland Godet, Arthur Bit-Monnot, Marc-Emmanuel Coupvent des Graviers, Christophe GUETTIER, Simon Lacroix

Keywords: PS: SAT, SMT and CP, PS: Routing, PS: Temporal planning, PS: Applications, PS: Optimization of spatio-temporal systems

Posthoc: The Visualisation Platform for Search 🔗

Kevin Zheng, Daniel Harabor, Michael Wybrow

Keywords: PS: Applications

Analyzing Launch Operations using the Spaceport Throughput Analysis Resource (STAR) 🔗

Jeremy Frank, Richard Levinson, Vijayakumar Baskaran, Jeffrey S Brink

Keywords: PS: Applications, PS: Scheduling, PS: SAT, SMT and CP

DynTaskMAS: A Dynamic Task Graph-driven Framework for Asynchronous and Parallel LLM-based Multi-Agent Systems 🔗

Junwei Yu, Yepeng Ding, Hiroyuki Sato

Keywords: PS: Planning with large language models, PS: Distributed and multi-agent planning, PS: Plan execution and monitoring, PS: Scheduling

HDDLGym: A Tool for Studying Multi-Agent Hierarchical Problems Defined in HDDL with OpenAI Gym 🔗

Ngoc La, Ruaridh Mon-Williams, Julie Shah

Keywords: PS: Planning with Hierarchical Task Networks (HTN), PS: Planning with Markov decision process models (MDPs, POMDPs), PS: Multi-agent path-finding

Robotics and Control Theory

A* for Bounding Shortest Paths in the Graphs of Convex Sets 🔗

Kaarthik Sundar, Sivakumar Rathinam

Keywords: PS: Mixed discrete/continuous planning, ROB: Motion and path planning

Safe Interval Randomized Path Planinng For Manipulators 🔗

Nuraddin Kerimov, Aleksandr Onegin, Konstantin Yakovlev

Keywords: PS: Search in planning and scheduling, ROB: Motion and path planning

Abstract Models

New Exact Methods for Solving Quadratic Traveling Salesman Problem 🔗

Yuxiao Chen, Anubhav Singh, Ryo Kuroiwa, Chris Beck

Keywords: PS: Routing, PS: Mathematical programming, PS: Search in planning and scheduling

How Good is Perfect? On the Incompleteness of A* for Total-Order HTN Planning 🔗

Mohammad Yousefi, Mario Schmautz, Patrik Haslum, Pascal Tobias Bercher

Keywords: PS: Planning with Hierarchical Task Networks (HTN), PS: Search in planning and scheduling

A Formalism for Optimal Search with Dynamic Heuristics 🔗

Remo Christen, Florian Pommerening, Clemens Büchner, Malte Helmert

Keywords: PS: Classical (fully-observable, deterministic) planning, PS: Search in planning and scheduling, PS: Theoretical foundations of planning

Pseudo-Boolean Proof Logging for Optimal Classical Planning 🔗

Simon Dold, Malte Helmert, Jakob Nordström, Gabriele Röger, Tanja Schindler

Keywords: PS: Classical (fully-observable, deterministic) planning, PS: Theoretical foundations of planning

Delete-Free Planning with Object Creation is Undecidable 🔗

Augusto B. Corrêa

Keywords: PS: Classical (fully-observable, deterministic) planning, PS: Theoretical foundations of planning

Cost-Optimal FOND Planning as Bi-Objective Best-First Search 🔗

Diego Aineto, Enrico Scala

Keywords: PS: Fully observable non-deterministic planning

Parallelizing Multi-objective A* Search 🔗

Saman Ahmadi, Nathan R. Sturtevant, Andrea Raith, Daniel Harabor, Mahdi Jalili

Keywords: PS: Search in planning and scheduling

Partially Observable Monte-Carlo Graph Search 🔗

YANG YOU, Vincent Thomas, Alex Schutz, Robert Skilton, Nick Hawes, Olivier Buffet

Keywords: PS: Planning with Markov decision process models (MDPs, POMDPs), PS: Planning under uncertainty, PS: Partially observable planning

Howard's Policy Iteration is Subexponential for Deterministic Markov Decision Problems with Rewards of Fixed Bit-size and Arbitrary Discount Factor 🔗

Dibyangshu Mukherjee, Shivaram Kalyanakrishnan

Keywords: PS: Planning with Markov decision process models (MDPs, POMDPs), PS: Infinite-horizon optimal control problems, PS: Theoretical foundations of planning

Strategies to Improve Goal Selection in Satisficing Oversubscription Planning 🔗

Angel Garcia Olaya, Patricia J. Riddle, Mike Barley

Keywords: PS: Classical (fully-observable, deterministic) planning

Going Topological in Multi-risk Extended Markov Ratio Decision Processes 🔗

Alexander Zadorojniy, Orit Davidovich, Takayuki Osogami

Keywords: PS: Planning with Markov decision process models (MDPs, POMDPs), PS: Mathematical programming, PS: Theoretical foundations of planning

On Using Lazy Greedy Best-First Search with Subgoaling Relaxation in Numeric Planning Problems 🔗

Enrico Scala, Luigi Bonassi

Keywords: PS: Mixed discrete/continuous planning

On Generating Robust Plans and Linear Execution Strategies in Planning Against Nature 🔗

Lukas Chrpa, Erez Karpas

Keywords: PS: Planning under uncertainty, PS: Search in planning and scheduling

Automating the Generation of Prompts for LLM-based Action Choice in PDDL Planning 🔗

Katharina Stein, Daniel Fišer, Jörg Hoffmann, Alexander Koller

Keywords: PS: Planning with large language models

On Picking Good Policies: Leveraging Action-Policy Testing in Policy Training 🔗

Jan Eisenhut, Daniel Fišer, Isabel Valera, Jörg Hoffmann

Keywords: PS: Learning for planning and scheduling, PS: Classical (fully-observable, deterministic) planning

Platform-Aware Mission Planning 🔗

Stefan Panjkovic, Alessandro Cimatti, Andrea Micheli, Stefano Tonetta

Keywords: PS: Temporal planning, PS: SAT, SMT and CP, PS: Plan execution and monitoring, PS: Model checking for trust, safety and robustness

Potential Heuristics: Weakening Consistency Constraints 🔗

Pascal Lauer, Daniel Fišer

Keywords: PS: Classical (fully-observable, deterministic) planning

Observation Adaptation via Annealed Importance Resampling for Partially Observable Markov Decision Processes 🔗

Yunuo Zhang, Baiting Luo, Ayan Mukhopadhyay, Abhishek Dubey

Keywords: PS: Planning under uncertainty, PS: Planning with Markov decision process models (MDPs, POMDPs), PS: Partially observable planning

Tight Bounds for Lifted HTN Plan Verification and Bounded Plan Existence 🔗

Pascal Lauer, S.T. Lin, Pascal Tobias Bercher

Keywords: PS: Planning with Hierarchical Task Networks (HTN)

Alternation-Based Novelty Search 🔗

Augusto B. Corrêa, Jendrik Seipp

Keywords: PS: Classical (fully-observable, deterministic) planning

Landmark Generation in HTN Planning Revisited 🔗

Victor Scherer Putrich, Felipe Meneguzzi, André Grahl Pereira

Keywords: PS: Planning with Hierarchical Task Networks (HTN)

Continuing the Quest for Polynomial Time Heuristics in PDDL Input Size: Tractable Cases for Lifted $h^{add}$ 🔗

Pascal Lauer, Alvaro Torralba, Daniel Höller, Jörg Hoffmann

Keywords: PS: Model-based reasoning, PS: Classical (fully-observable, deterministic) planning

Hardness of Chosen Length Planning Games and Regular Fixed Methods FOND HTN Planning 🔗

P. Maurice Dekker, Gregor Behnke

Keywords: PS: Fully observable non-deterministic planning, PS: Planning with Hierarchical Task Networks (HTN)

On the Notion of Plan Quality for PDDL+ 🔗

Francesco Percassi, Enrico Scala, Mauro Vallati

Keywords: PS: Mixed discrete/continuous planning

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

Keywords: PS: Planning with Markov decision process models (MDPs, POMDPs), PS: Infinite-horizon optimal control problems

Agent Planning Programs as Non-deterministic Planning under Fairness 🔗

Nitin Yadav, Sebastian Sardina, Hector Geffner

Keywords: PS: Fully observable non-deterministic planning

A Sampling Approach to Planning with Infinite Domain Control Variables 🔗

Ángel Aso-Mollar, Diego Aineto, Enrico Scala, Eva Onaindia

Keywords: PS: Classical (fully-observable, deterministic) planning, PS: Search in planning and scheduling

Initial Condition Retrieving for Hybrid and Numeric Planning Problems 🔗

Matteo Cardellini, Francesco Percassi, Marco Maratea, Mauro Vallati

Keywords: PS: Mixed discrete/continuous planning

SibylSatOpt: a MaxSAT-based Greedy Optimal Search for TOHTN Planning 🔗

Gaspard Quenard, Damien Pellier, Humbert FIORINO

Keywords: PS: Planning with Hierarchical Task Networks (HTN), PS: SAT, SMT and CP

Machine Learning

Leveraging Action Relational Structures for Integrated Learning and Planning 🔗

Ryan Xiao Wang, Felipe Trevizan

Keywords: PS: Learning for planning and scheduling, PS: Classical (fully-observable, deterministic) planning, PS: Search in planning and scheduling

Per-Domain Generalizing Policies: On Validation Instances and Scaling Behavior 🔗

Timo P. Gros, Nicola J. Müller, Daniel Fišer, Isabel Valera, Verena Wolf, Jörg Hoffmann

Keywords: PS: Generalized planning

Rack Position Optimization in Large-Scale Heterogeneous Data Centers 🔗

Chang-Lin Chen, Jiayu Chen, Tian Lan, Zhaoxia Zhao, Hongbo Dong, Vaneet Aggarwal

Keywords: PS: Applications, PS: Learning for planning and scheduling

Learning Lifted STRIPS Models from Action Traces alone: A Simple, General, and Scalable Solution 🔗

Jonas Gösgens, Niklas Jansen, Hector Geffner

Keywords: PS: Learning for planning and scheduling

Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation 🔗

Sukai Huang, Nir Lipovetzky

Keywords: PS: Planning with large language models

Automating the Generation of Prompts for LLM-based Action Choice in PDDL Planning 🔗

Katharina Stein, Daniel Fišer, Jörg Hoffmann, Alexander Koller

Keywords: PS: Planning with large language models

Instance-based Approximation Guarantees for Graph-based Nearest Neighbor Search 🔗

Yannick Bosch, Sabine Storandt

Keywords: PS: Search in planning and scheduling, PS: Routing

On Picking Good Policies: Leveraging Action-Policy Testing in Policy Training 🔗

Jan Eisenhut, Daniel Fišer, Isabel Valera, Jörg Hoffmann

Keywords: PS: Learning for planning and scheduling, PS: Classical (fully-observable, deterministic) planning

Learning Efficiency Meets Symmetry Breaking 🔗

Yingbin Bai, Sylvie Thiebaux, Felipe Trevizan

Keywords: PS: Learning for planning and scheduling

On Planning Through LLMs 🔗

Mattia Chiari, Luca Putelli, Nicholas Rossetti, Ivan Serina, Alfonso Gerevini

Keywords: PS: Learning for planning and scheduling

HDDLGym: A Tool for Studying Multi-Agent Hierarchical Problems Defined in HDDL with OpenAI Gym 🔗

Ngoc La, Ruaridh Mon-Williams, Julie Shah

Keywords: PS: Planning with Hierarchical Task Networks (HTN), PS: Planning with Markov decision process models (MDPs, POMDPs), PS: Multi-agent path-finding

Knowledge Engineering

Quality Diversity for Variational Quantum Circuit Optimization 🔗

Maximilian Zorn, Jonas Stein, Maximilian Balthasar Mansky, Philipp Altmann, Michael Kölle, Claudia Linnhoff-Popien

Keywords: PS: Local search and evolutionary programming, PS: Sub-modular and gradient-free optimization

On the Gains from Using Action Observations in Domain Repair 🔗

Alba Gragera, Raquel Fuentetaja, Angel Garcia Olaya, Fernando Fernández

Keywords: PS: Planning with incomplete models

Is This Plan Necessarily Redundant? On the Computational Complexity of Unobserved Domain Learning 🔗

Pascal Bachor, P. Maurice Dekker, Gregor Behnke

Keywords: PS: Learning for planning and scheduling, PS: Partially observable planning, PS: Theoretical foundations of planning

Knowledge Engineering for Planning and Scheduling in the LLM Era 🔗

Mauro Vallati, Roman Barták, Lukas Chrpa, Thomas Leo McCluskey, Ron Petrick

Keywords: PS: Applications

HTN Plan Repair Algorithms Compared: Strengths and Weaknesses of Different Methods 🔗

Paul Zaidins, Robert P. Goldman, Ugur Kuter, Dana S. Nau, Mark Roberts

Keywords: PS: Planning with Hierarchical Task Networks (HTN), PS: Plan execution and monitoring

LTLf Adaptive Synthesis for Multi-Tier Goals in Nondeterministic Domains 🔗

Giuseppe De Giacomo, Gianmarco Parretti, Shufang Zhu

Keywords: PS: Model-based reasoning, PS: Fully observable non-deterministic planning

Initial Condition Retrieving for Hybrid and Numeric Planning Problems 🔗

Matteo Cardellini, Francesco Percassi, Marco Maratea, Mauro Vallati

Keywords: PS: Mixed discrete/continuous planning