Foundations of Artificial Intelligence (FAI) Group E-mail: danfis@danfis.cz, danfis@cs.uni-saarland.de |
|
Publications
Journal Papers
Boosting Optimal Symbolic Planning: Operator-Potential Heuristics
(pdf,
doi)
Daniel Fišer, Álvaro Torralba, Jörg Hoffmann
Artificial Intelligence Journal (2024)
The 2023 International Planning Competition
(doi)
Ayal Taitler, Ron Alford, Joan Espasa, Gregor Behnke, Daniel Fišer,
Michael Gimelfarb, Florian Pommerening, Scott Sanner, Enrico Scala,
Dominik Schreiber, Javier Segovia-Aguas, Jendrik Seipp
AI Magazine (2024)
Conference Papers
Iterative Oversubscription Planning with Goal-Conflict Explanations: Scaling Up
Through Policy-Guidance Approximation
Rebecca Eifler, Daniel Fišer, Aleena Siji, Jörg Hoffmann
ECAI 2024
Towards Feasible Higher-Dimensional Potential Heuristics
(doi)
Daniel Fišer, Marcel Steinmetz
ICAPS 2024
New Fuzzing Biases for Action Policy Testing
(doi)
Jan Eisenhut, Xandra Schuler, Daniel Fišer, Daniel Höller, Maria Christakis, Jörg Hoffmann
ICAPS 2024
Gaifman Graphs in Lifted Planning
(doi)
Rostislav Horčík, Daniel Fišer
ECAI 2023
A Landmark-Cut Heuristic for Lifted Optimal Planning
(doi)
Julia Wichlacz, Daniel Höller, Daniel Fišer, Jörg Hoffmann
ECAI 2023
Operator Pruning using Lifted Mutex Groups via Compilation on Lifted Level
(pdf,
slides,
doi)
Daniel Fišer
ICAPS 2023
This paper received ICAPS’23 Best Paper Award, Runner Up
Operator-Potentials in Symbolic Search: From Forward to Bi-Directional Search
(link,
doi)
Daniel Fišer, Álvaro Torralba, Jörg Hoffmann
ICAPS 2022
Beyond Stars - Generalized Topologies for Decoupled Search
(link,
doi)
Daniel Gnad, Álvaro Torralba, Daniel Fišer
ICAPS 2022
Debugging a Policy: Automatic Action-Policy Testing in AI Planning
(link,
doi)
Marcel Steinmetz, Daniel Fišer, Hasan Ferit Enişer, Patrick Ferber, Timo Gros,
Philippe Heim, Daniel Höller, Xandra Schuler, Valentin Wüstholz,
Maria Christakis, Joerg Hoffmann
ICAPS 2022
Operator-Potential Heuristics for Symbolic Search
(pdf,
appendix,
link,
doi)
Daniel Fišer, Álvaro Torralba, Jörg Hoffmann
AAAI 2022
This paper received Honorable Mention in AAAI’22 Outstanding Paper Awards
Homomorphisms of Lifted Planning Tasks: The Case for Delete-free Relaxation Heuristics
(pdf,
link,
doi)
Rostislav Horčík, Daniel Fišer, Álvaro Torralba
AAAI 2022
Custom-Design of FDR Encodings: The Case of Red-Black Planning
(pdf,
link,
doi)
Daniel Fišer, Daniel Gnad, Michael Katz, Jörg Hoffmann
IJCAI 2021
Polynomial-Time in PDDL Input Size: Making the Delete Relaxation Feasible for Lifted Planning
(link,
doi)
Pascal Lauer, Álvaro Torralba, Daniel Fišer, Daniel Höller, Julia Wichlacz, Jörg Hoffmann
IJCAI 2021
On the Reversibility of Actions in Planning
(link,
doi)
Michael Morak, Lukáš Chrpa, Wolfgang Faber, Daniel Fišer
KR 2020, 652-661
Strengthening Potential Heuristics with Mutexes and Disambiguations
(pdf,
link,
doi)
Daniel Fišer, Rostislav Horčík, Antonín Komenda
ICAPS 2020, 124-133
Lifted Fact-Alternating Mutex Groups and Pruned Grounding of Classical Planning Problems
(pdf,
doi)
Daniel Fišer
AAAI 2020, 9835-9842
Operator Mutexes and Symmetries for Simplifying Planning Tasks
(pdf,
slides,
poster,
doi)
Daniel Fišer, Álvaro Torralba, Alexander Shleyfman
AAAI 2019, 7586-7593
Privacy Leakage of Search-based Multi-Agent Planning Algorithms
(link,
doi)
Michal Štolba, Daniel Fišer, Antonín Komenda
ICAPS 2019, 482-490
Cost Partitioning for Multi-agent Planning
(pdf,bibtex)
Michal Štolba, Michaela Urbanovská, Daniel Fišer, Antonín Komenda
ICAART 2019, Vol. 2, 40-49
A General Approach to Distributed and Privacy-Preserving Heuristic
Computation
(link)
Michal Štolba, Michaela Urbanovská, Daniel Fišer, Antonín Komenda
Agents and Artificial Intelligence 2019, 55-71
Fact-Alternating Mutex Groups for Classical Planning (Extended Abstract)
(pdf,
doi)
Daniel Fišer, Antonín Komenda
IJCAI 2018, Journal track, 5603-5607
Concise Finite-Domain Representations for Factored MA-PDDL Planning Tasks
(pdf,
doi,
bibtex)
Daniel Fišer, Antonín Komenda
ICAART 2018, Vol. 2, 306-313
Potential Heuristics for Multi-Agent Planning
(pdf,
bibtex)
Michal Štolba, Daniel Fišer, Antonín Komenda
ICAPS 2016, 308-316
Admissible Landmark Heuristic for Multi-Agent Planning
(pdf,
bibtex)
Michal Štolba, Daniel Fišer, Antonín Komenda
ICAPS 2015, 211-219
Workshop Papers / Extended Abstracts
Automating the Generation of Prompts for LLM-based Action Choice in PDDL Planning
Katharina Stein, Daniel Fišer, Jörg Hoffmann, and Alexander Koller
Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS), at ICAPS’24.
Action Policy Explanations in Oversubscription Planning
(pdf)
Aleena Siji, Rebecca Eifler, Daniel Fišer, and Jörg Hoffmann
International Workshop of Human-Aware and Explainable Planning (HAXP’23), at ICAPS’23.
Action Policy Testing with Heuristic-Based Bias Functions
Xandra Schuler, Jan Eisenhut, Daniel Höller, Daniel Fišer, and Jörg Hoffmann
Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS’23), at ICAPS’23.
Introducing Operator-Potential Heuristics for Symbolic Search
(link)
Daniel Fišer, Álvaro Torralba, Jörg Hoffmann
HSDIP 2021
Comparison of RPG-based FF and DTG-based FF Disrtibuted Heuristics
(pdf,
bibtex)
Michal Štolba, Daniel Fišer, Antonín Komenda
DMAP 2015, 77-82
A Light-Weight Robot Simulator for Modular Robotics
(doi,
bibtex)
Vojtěch Vonásek, Daniel Fišer, Karel Košnar, Libor Přeučil
First International Workshop, MESAS 2014, 206-216
Bringing Reality to Evolution of Modular Robots: Bio-Inspired Techniques
for Building a Simulation Environment in the SYMBRION Project
(pdf,
bibtex)
Martin Saska, Vojtěch Vonásek, Miroslav Kulich, Daniel Fišer, Tomáš Krajnık, Libor Přeučil
Reconfigurable Modular Robotics: Challenges of Mechatronic and Bio-Chemo 2011
PhD thesis: Mutual Exclusion State Invariants in Classical Planning (defended 2021)
Master’s thesis: Inference of State Invariants for Domain-Independent Planning (2016), Dean award for an exceptional master thesis
Software
-
cpddl — library with algorithms for automated planning
-
pddl-data — repository of (MA-)PDDL problems.
-
maplan — (MA-)PDDL planner.
-
libccd — library for collision detection between convex shapes.
-
gnn — library implementing several growing neural network algorithms.
-
cu — C Unit Testing Framework
-
boruvka — C library implementing some basic mathematical routines and low level algorithms.
-
QShowDiff — a tool for visualisation of diffs generated from various VCS systems.
-
pitweb — pythonic web interface for git repositories.
-
opts — library for parsing command line options.
-
Sim — a robotic simulator.
-
SVT — a tool for visualization of 2D and 3D objects.