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ORCIDJörg Hoffmann 0001
Person information
- affiliation (since 2012): Saarland University, Department of Computer Science, Saarbrücken, Germany
- affiliation (since 2009): INRIA, Nancy, France
- affiliation (since 2008): SAP Research Karlsruhe, Germany
- affiliation (former): University of Innsbruck, Semantic Technology Institute, Austria
- affiliation (2006): Cornell University, Ithaca, NY, USA
- affiliation (2004 - 2006): Max Planck Institute for Computer Science, Saarbrücken, Germany
- affiliation (PhD 2002): University of Freiburg, Department of Computer Science, Germany
Other persons with the same name
- Jörg Hoffmann — disambiguation page
- Jörg Hoffmann 0002 — Bauhaus University Weimar, Faculty of Media, Germany
- Jörg Hoffmann 0003 — Kaiserslautern University of Technology, Germany
- Jörg Hoffmann 0004 — German Federal Research Institute for Agriculture, Braunschweig, Germany
- Jörg Hoffmann 0005 — University of Bonn, Germany
- Jörg Hoffmann 0006
![[0000-0003-4493-094X]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-4493-094X")
— RWTH Aachen University, Germany - Jörg Hoffmann 0007 — Julius Kühn-Institut - Federal Research Centre for Cultivated Plants, Quedlinburg, Germany
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2020 – today
- 2024
[c160]Jan Eisenhut, Xandra Schuler, Daniel Fiser, Daniel Höller, Maria Christakis, Jörg Hoffmann:
New Fuzzing Biases for Action Policy Testing. ICAPS 2024: 162-167- [c159]Marcel Vinzent, Jörg Hoffmann:
Neural Action Policy Safety Verification: Applicablity Filtering. ICAPS 2024: 607-612 - [i23]Jayanta Mandi, Marco Foschini, Daniel Höller, Sylvie Thiébaux, Jörg Hoffmann, Tias Guns:
Decision-Focused Learning to Predict Action Costs for Planning. CoRR abs/2408.06876 (2024) - 2023
- [j40]Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz:
Analyzing neural network behavior through deep statistical model checking. Int. J. Softw. Tools Technol. Transf. 25(3): 407-426 (2023) - [j39]Timo P. Gros, Joschka Groß, Daniel Höller, Jörg Hoffmann, Michaela Klauck, Hendrik Meerkamp, Nicola J. Müller, Lukas Schaller, Verena Wolf:
DSMC Evaluation Stages: Fostering Robust and Safe Behavior in Deep Reinforcement Learning - Extended Version. ACM Trans. Model. Comput. Simul. 33(4): 17:1-17:28 (2023) - [c158]Marcel Vinzent, Siddhant Sharma, Jörg Hoffmann:
Neural Policy Safety Verification via Predicate Abstraction: CEGAR. AAAI 2023: 15188-15196 - [c157]Jan Eisenhut, Álvaro Torralba, Maria Christakis, Jörg Hoffmann:
Automatic Metamorphic Test Oracles for Action-Policy Testing. ICAPS 2023: 109-117 - [c156]Philipp Sauer, Marcel Steinmetz, Robert Künnemann, Jörg Hoffmann:
Lifted Stackelberg Planning. ICAPS 2023: 370-374 - [c155]Julia Wichlacz, Daniel Höller, Daniel Fiser, Jörg Hoffmann:
A Landmark-Cut Heuristic for Lifted Optimal Planning. ECAI 2023: 2623-2630 - [c154]Maria Christakis, Hasan Ferit Eniser, Jörg Hoffmann, Adish Singla, Valentin Wüstholz:
Specifying and Testing k-Safety Properties for Machine-Learning Models. IJCAI 2023: 4748-4757 - 2022
- [j38]Maximilian Fickert, Jörg Hoffmann:
Online Relaxation Refinement for Satisficing Planning: On Partial Delete Relaxation, Complete Hill-Climbing, and Novelty Pruning. J. Artif. Intell. Res. 73: 67-115 (2022) - [c153]Stefan Borgwardt, Jörg Hoffmann, Alisa Kovtunova, Markus Krötzsch, Bernhard Nebel, Marcel Steinmetz:
Expressivity of Planning with Horn Description Logic Ontologies. AAAI 2022: 5503-5511 - [c152]Daniel Fiser, Álvaro Torralba, Jörg Hoffmann:
Operator-Potential Heuristics for Symbolic Search. AAAI 2022: 9750-9757 - [c151]Marcel Steinmetz, Jörg Hoffmann, Alisa Kovtunova, Stefan Borgwardt:
Classical Planning with Avoid Conditions. AAAI 2022: 9944-9952 - [c150]Martim Brandao, Amanda Jane Coles, Andrew Coles, Jörg Hoffmann:
Merge and Shrink Abstractions for Temporal Planning. ICAPS 2022: 16-25 - [c149]Daniel Fiser, Álvaro Torralba, Jörg Hoffmann:
Operator-Potentials in Symbolic Search: From Forward to Bi-directional Search. ICAPS 2022: 80-89 - [c148]Thorsten Klößner, Marcel Steinmetz, Álvaro Torralba, Jörg Hoffmann:
Pattern Selection Strategies for Pattern Databases in Probabilistic Planning. ICAPS 2022: 184-192 - [c147]Marcel Steinmetz, Daniel Fiser, Hasan Ferit Eniser, Patrick Ferber, Timo P. Gros, Philippe Heim, Daniel Höller, Xandra Schuler, Valentin Wüstholz, Maria Christakis, Jörg Hoffmann:
Debugging a Policy: Automatic Action-Policy Testing in AI Planning. ICAPS 2022: 353-361 - [c146]Marcel Vinzent, Marcel Steinmetz, Jörg Hoffmann:
Neural Network Action Policy Verification via Predicate Abstraction. ICAPS 2022: 371-379 - [c145]Patrick Ferber, Florian Geißer, Felipe W. Trevizan, Malte Helmert, Jörg Hoffmann:
Neural Network Heuristic Functions for Classical Planning: Bootstrapping and Comparison to Other Methods. ICAPS 2022: 583-587 - [c144]Rebecca Eifler, Martim Brandao, Amanda Jane Coles, Jeremy Frank, Jörg Hoffmann:
Evaluating Plan-Property Dependencies: A Web-Based Platform and User Study. ICAPS 2022: 687-691 - [c143]Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Maximilian A. Köhl, Verena Wolf:
MoGym: Using Formal Models for Training and Verifying Decision-making Agents. CAV (2) 2022: 430-443 - [c142]Stefan Borgwardt, Jörg Hoffmann, Alisa Kovtunova, Markus Krötzsch, Bernhard Nebel, Marcel Steinmetz:
Expressivity of Planning with Horn Description Logic Ontologies (Extended Abstract). Description Logics 2022 - [c141]Rebecca Eifler, Jeremy Frank, Jörg Hoffmann:
Explaining Soft-Goal Conflicts through Constraint Relaxations. IJCAI 2022: 4621-4627 - [c140]Julia Wichlacz, Daniel Höller, Jörg Hoffmann:
Landmark Heuristics for Lifted Classical Planning. IJCAI 2022: 4665-4671 - [c139]Hasan Ferit Eniser, Timo P. Gros, Valentin Wüstholz, Jörg Hoffmann, Maria Christakis:
Metamorphic relations via relaxations: an approach to obtain oracles for action-policy testing. ISSTA 2022: 52-63 - [c138]David Groß, Michaela Klauck, Timo P. Gros, Marcel Steinmetz, Jörg Hoffmann, Stefan Gumhold:
Glyph-Based Visual Analysis of Q-Leaning Based Action Policy Ensembles on Racetrack. IV 2022: 1-10 - [c137]Daniel Heller, Patrick Ferber, Julian Bitterwolf, Matthias Hein, Jörg Hoffmann:
Neural Network Heuristic Functions: Taking Confidence into Account. SOCS 2022: 223-228 - [d1]Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Maximilian A. Köhl, Verena Wolf:
Artifact for the Tool Paper: MoGym: Using Formal Models for Training and Verifying Decision-making Agents. Zenodo, 2022
- [i22]Stefan Borgwardt, Jörg Hoffmann, Alisa Kovtunova, Markus Krötzsch, Bernhard Nebel, Marcel Steinmetz:
Expressivity of Planning with Horn Description Logic Ontologies (Technical Report). CoRR abs/2203.09361 (2022) - [i21]Maria Christakis, Hasan Ferit Eniser, Jörg Hoffmann, Adish Singla, Valentin Wüstholz:
Specifying and Testing k-Safety Properties for Machine-Learning Models. CoRR abs/2206.06054 (2022) - 2021
- [c136]Álvaro Torralba, Patrick Speicher, Robert Künnemann, Marcel Steinmetz, Jörg Hoffmann:
Faster Stackelberg Planning via Symbolic Search and Information Sharing. AAAI 2021: 11998-12006 - [c135]Maximilian Fickert, Ivan Gavran, Ivan Fedotov, Jörg Hoffmann, Rupak Majumdar, Wheeler Ruml:
Choosing the Initial State for Online Replanning. AAAI 2021: 12311-12319 - [c134]Thorsten Klößner, Jörg Hoffmann, Marcel Steinmetz, Álvaro Torralba:
Pattern Databases for Goal-Probability Maximization in Probabilistic Planning. ICAPS 2021: 201-209 - [c133]Maria Christakis, Hasan Ferit Eniser, Holger Hermanns, Jörg Hoffmann, Yugesh Kothari, Jianlin Li, Jorge A. Navas, Valentin Wüstholz:
Automated Safety Verification of Programs Invoking Neural Networks. CAV (1) 2021: 201-224 - [c132]Daniel Gnad, Jan Eisenhut, Alberto Lluch-Lafuente, Jörg Hoffmann:
Model Checking ømega-Regular Properties with Decoupled Search. CAV (2) 2021: 411-434 - [c131]Stefan Borgwardt, Jörg Hoffmann, Alisa Kovtunova, Marcel Steinmetz:
Making DL-Lite Planning Practical (Extended Abstract). Description Logics 2021 - [c130]Frederik Wiehr, Anke Hirsch, Lukas Schmitz, Nina Knieriemen, Antonio Krüger, Alisa Kovtunova, Stefan Borgwardt, Ernie Chang, Vera Demberg, Marcel Steinmetz, Jörg Hoffmann:
Why Do I Have to Take Over Control? Evaluating Safe Handovers with Advance Notice and Explanations in HAD. ICMI 2021: 308-317 - [c129]Daniel Fiser, Daniel Gnad, Michael Katz, Jörg Hoffmann:
Custom-Design of FDR Encodings: The Case of Red-Black Planning. IJCAI 2021: 4054-4061 - [c128]Pascal Lauer, Álvaro Torralba, Daniel Fiser, Daniel Höller, Julia Wichlacz, Jörg Hoffmann:
Polynomial-Time in PDDL Input Size: Making the Delete Relaxation Feasible for Lifted Planning. IJCAI 2021: 4119-4126 - [c127]Valentin Seimetz, Rebecca Eifler, Jörg Hoffmann:
Learning Temporal Plan Preferences from Examples: An Empirical Study. IJCAI 2021: 4160-4166 - [c126]Stefan Borgwardt, Jörg Hoffmann, Alisa Kovtunova, Marcel Steinmetz:
Making DL-Lite Planning Practical. KR 2021: 641-645 - [c125]Timo P. Gros, Daniel Höller, Jörg Hoffmann, Michaela Klauck, Hendrik Meerkamp, Verena Wolf:
DSMC Evaluation Stages: Fostering Robust and Safe Behavior in Deep Reinforcement Learning. QEST 2021: 197-216 - [c124]Thorsten Klößner, Jörg Hoffmann:
Pattern Databases for Stochastic Shortest Path Problems. SOCS 2021: 131-135 - [c123]Julia Wichlacz, Daniel Höller, Jörg Hoffmann:
Landmark Heuristics for Lifted Planning - Extended Abstract. SOCS 2021: 242-244 - 2020
- [j37]Michaela Klauck, Marcel Steinmetz, Jörg Hoffmann, Holger Hermanns:
Bridging the Gap Between Probabilistic Model Checking and Probabilistic Planning: Survey, Compilations, and Empirical Comparison. J. Artif. Intell. Res. 68: 247-310 (2020) - [c122]Rebecca Eifler, Michael Cashmore, Jörg Hoffmann, Daniele Magazzeni, Marcel Steinmetz:
A New Approach to Plan-Space Explanation: Analyzing Plan-Property Dependencies in Oversubscription Planning. AAAI 2020: 9818-9826 - [c121]Maximilian Fickert, Tianyi Gu, Leonhard Staut, Wheeler Ruml, Jörg Hoffmann, Marek Petrik:
Beliefs We Can Believe in: Replacing Assumptions with Data in Real-Time Search. AAAI 2020: 9827-9834 - [c120]Jörg Hoffmann, Holger Hermanns, Michaela Klauck, Marcel Steinmetz, Erez Karpas, Daniele Magazzeni:
Let's Learn Their Language? A Case for Planning with Automata-Network Languages from Model Checking. AAAI 2020: 13569-13575 - [c119]Arne Köhn, Julia Wichlacz, Álvaro Torralba, Daniel Höller, Jörg Hoffmann, Alexander Koller:
Generating Instructions at Different Levels of Abstraction. COLING 2020: 2802-2813 - [c118]Patrick Ferber, Malte Helmert, Jörg Hoffmann:
Neural Network Heuristics for Classical Planning: A Study of Hyperparameter Space. ECAI 2020: 2346-2353 - [c117]Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz:
Deep Statistical Model Checking. FORTE 2020: 96-114 - [c116]Rebecca Eifler, Marcel Steinmetz, Álvaro Torralba, Jörg Hoffmann:
Plan-Space Explanation via Plan-Property Dependencies: Faster Algorithms & More Powerful Properties. IJCAI 2020: 4091-4097 - [c115]Timo P. Gros, David Groß, Stefan Gumhold, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz:
TraceVis: Towards Visualization for Deep Statistical Model Checking. ISoLA (4) 2020: 27-46 - [c114]Rasha Faqeh, Christof Fetzer, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Maximilian A. Köhl, Marcel Steinmetz, Christoph Weidenbach:
Towards Dynamic Dependable Systems Through Evidence-Based Continuous Certification. ISoLA (2) 2020: 416-439 - [c113]Timo P. Gros, Daniel Höller, Jörg Hoffmann, Verena Wolf:
Tracking the Race Between Deep Reinforcement Learning and Imitation Learning. QEST 2020: 11-17 - [c112]Arne Köhn, Julia Wichlacz, Christine Schäfer, Álvaro Torralba, Jörg Hoffmann, Alexander Koller:
MC-Saar-Instruct: a Platform for Minecraft Instruction Giving Agents. SIGdial 2020: 53-56 - [c111]Julia Wichlacz, Daniel Höller, Álvaro Torralba, Jörg Hoffmann:
Applying Monte-Carlo Tree Search in HTN Planning. SOCS 2020: 82-90 - [c110]Christel Baier, Maria Christakis, Timo P. Gros, David Groß, Stefan Gumhold, Holger Hermanns, Jörg Hoffmann, Michaela Klauck:
Lab Conditions for Research on Explainable Automated Decisions. TAILOR 2020: 83-90 - [p2]Jörg Hoffmann, Malte Helmert, Daniel Gnad, Florian Pommerening:
Planen. Handbuch der Künstlichen Intelligenz 2020: 395-428 - [e4]J. Christopher Beck, Olivier Buffet, Jörg Hoffmann, Erez Karpas, Shirin Sohrabi:
Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling, Nancy, France, October 26-30, 2020. AAAI Press 2020, ISBN 978-1-57735-824-4 [contents] - [i20]Timo P. Gros, Daniel Höller, Jörg Hoffmann, Verena Wolf:
Tracking the Race Between Deep Reinforcement Learning and Imitation Learning - Extended Version. CoRR abs/2008.00766 (2020) - [i19]Arne Köhn, Julia Wichlacz, Álvaro Torralba, Daniel Höller, Jörg Hoffmann, Alexander Koller:
Generating Instructions at Different Levels of Abstraction. CoRR abs/2010.03982 (2020) - [i18]Frederik Wiehr, Anke Hirsch, Florian Daiber, Antonio Krüger, Alisa Kovtunova, Stefan Borgwardt, Ernie Chang, Vera Demberg, Marcel Steinmetz, Jörg Hoffmann:
Safe Handover in Mixed-Initiative Control for Cyber-Physical Systems. CoRR abs/2010.10967 (2020) - [i17]Rebecca Eifler, Jörg Hoffmann:
Iterative Planning with Plan-Space Explanations: A Tool and User Study. CoRR abs/2011.09705 (2020)
2010 – 2019
- 2019
- [j36]Dorin Shmaryahu, Guy Shani, Jörg Hoffmann:
Comparative criteria for partially observable contingent planning. Auton. Agents Multi Agent Syst. 33(5): 481-517 (2019) - [j35]Daniel Gnad, Jörg Hoffmann, Martin Wehrle:
Strong Stubborn Set Pruning for Star-Topology Decoupled State Space Search. J. Artif. Intell. Res. 65: 343-392 (2019) - [c109]Andrew Mitchell, Wheeler Ruml, Fabian Spaniol, Jörg Hoffmann, Marek Petrik:
Real-Time Planning as Decision-Making under Uncertainty. AAAI 2019: 2338-2345 - [c108]Rebecca Eifler, Maximilian Fickert, Jörg Hoffmann, Wheeler Ruml:
Refining Abstraction Heuristics during Real-Time Planning. AAAI 2019: 7578-7585 - [c107]Daniel Gnad, Jörg Hoffmann:
On the Relation between Star-Topology Decoupling and Petri Net Unfolding. ICAPS 2019: 172-180 - [c106]Frederik Schmitt, Daniel Gnad, Jörg Hoffmann:
Advanced Factoring Strategies for Decoupled Search Using Linear Programming. ICAPS 2019: 377-381 - [c105]Dorin Shmaryahu, Jörg Hoffmann, Guy Shani:
Comparative Criteria for Partially Observable Contingent Planning. AAMAS 2019: 1740-1742 - [c104]Jörg Hoffmann, Daniele Magazzeni:
Explainable AI Planning (XAIP): Overview and the Case of Contrastive Explanation (Extended Abstract). RW 2019: 277-282 - [c103]Patrick Speicher, Marcel Steinmetz, Jörg Hoffmann, Michael Backes, Robert Künnemann:
Towards automated network mitigation analysis. SAC 2019: 1971-1978 - 2018
- [j34]Daniel Gnad, Jörg Hoffmann:
Star-topology decoupled state space search. Artif. Intell. 257: 24-60 (2018) - [c102]Patrick Speicher, Marcel Steinmetz, Michael Backes, Jörg Hoffmann, Robert Künnemann:
Stackelberg Planning: Towards Effective Leader-Follower State Space Search. AAAI 2018: 6286-6293 - [c101]Michaela Klauck, Marcel Steinmetz, Jörg Hoffmann, Holger Hermanns:
Compiling Probabilistic Model Checking into Probabilistic Planning. ICAPS 2018: 150-154 - [c100]Dorin Shmaryahu, Guy Shani, Jörg Hoffmann, Marcel Steinmetz:
Simulated Penetration Testing as Contingent Planning. ICAPS 2018: 241-249 - [c99]Anna Wilhelm, Marcel Steinmetz, Jörg Hoffmann:
On Stubborn Sets and Planning with Resources. ICAPS 2018: 288-297 - [c98]Patrick Speicher, Marcel Steinmetz, Robert Künnemann, Milivoj Simeonovski, Giancarlo Pellegrino, Jörg Hoffmann, Michael Backes:
Formally Reasoning about the Cost and Efficacy of Securing the Email Infrastructure. EuroS&P 2018: 77-91 - [c97]Maximilian Fickert, Daniel Gnad, Jörg Hoffmann:
Unchaining the Power of Partial Delete Relaxation, Part II: Finding Plans with Red-Black State Space Search. IJCAI 2018: 4750-4756 - [c96]Marcel Steinmetz, Jörg Hoffmann:
LP Heuristics over Conjunctions: Compilation, Convergence, Nogood Learning. IJCAI 2018: 4837-4843 - [c95]Daniel Gnad, Patrick Dubbert, Alberto Lluch-Lafuente, Jörg Hoffmann:
Star-Topology Decoupling in SPIN. SPIN 2018: 103-114 - [r2]Jörg Hoffmann, Ingo Weber:
Web Service Composition. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - 2017
- [j33]Marcel Steinmetz, Jörg Hoffmann:
State space search nogood learning: Online refinement of critical-path dead-end detectors in planning. Artif. Intell. 245: 1-37 (2017) - [c94]Maximilian Fickert, Jörg Hoffmann:
Complete Local Search: Boosting Hill-Climbing through Online Relaxation Refinement. ICAPS 2017: 107-115 - [c93]Daniel Gnad, Álvaro Torralba, Alexander Shleyfman, Jörg Hoffmann:
Symmetry Breaking in Star-Topology Decoupled Search. ICAPS 2017: 125-134 - [c92]Patrick Speicher, Marcel Steinmetz, Daniel Gnad, Jörg Hoffmann, Alfonso Gerevini:
Beyond Red-Black Planning: Limited-Memory State Variables. ICAPS 2017: 269-273 - [c91]Marcel Steinmetz, Jörg Hoffmann:
Critical-Path Dead-End Detection versus NoGoods: Offline Equivalence and Online Learning. ICAPS 2017: 283-287 - [c90]Daniel Gnad, Valerie Poser, Jörg Hoffmann:
Beyond Forks: Finding and Ranking Star Factorings for Decoupled Search. IJCAI 2017: 4310-4316 - [c89]Marcel Steinmetz, Jörg Hoffmann:
Search and Learn: On Dead-End Detectors, the Traps they Set, and Trap Learning. IJCAI 2017: 4398-4404 - [c88]Maximilian Fickert, Jörg Hoffmann:
Ranking Conjunctions for Partial Delete Relaxation Heuristics in Planning. SOCS 2017: 38-46 - [c87]Daniel Gnad, Álvaro Torralba, Jörg Hoffmann:
Symbolic Leaf Representation in Decoupled Search. SOCS 2017: 124-128 - [i16]Michael Backes, Jörg Hoffmann, Robert Künnemann, Patrick Speicher, Marcel Steinmetz:
Simulated Penetration Testing and Mitigation Analysis. CoRR abs/1705.05088 (2017) - 2016
- [j32]Maximilian Fickert, Jörg Hoffmann, Marcel Steinmetz:
Combining the Delete Relaxation with Critical-Path Heuristics: A Direct Characterization. J. Artif. Intell. Res. 56: 269-327 (2016) - [j31]Marcel Steinmetz, Jörg Hoffmann, Olivier Buffet:
Goal Probability Analysis in Probabilistic Planning: Exploring and Enhancing the State of the Art. J. Artif. Intell. Res. 57: 229-271 (2016) - [j30]Vera Demberg, Jörg Hoffmann, David M. Howcroft, Dietrich Klakow, Álvaro Torralba:
Search Challenges in Natural Language Generation with Complex Optimization Objectives. Künstliche Intell. 30(1): 63-69 (2016) - [c86]Marcel Steinmetz, Jörg Hoffmann:
Towards Clause-Learning State Space Search: Learning to Recognize Dead-Ends. AAAI 2016: 760-768 - [c85]Jeanette Daum, Álvaro Torralba, Jörg Hoffmann, Patrik Haslum, Ingo Weber:
Practical Undoability Checking via Contingent Planning. ICAPS 2016: 106-114 - [c84]Marcel Steinmetz, Jörg Hoffmann, Olivier Buffet:
Revisiting Goal Probability Analysis in Probabilistic Planning. ICAPS 2016: 299-307 - [c83]Maximilian Schwenger, Álvaro Torralba, Jörg Hoffmann, David M. Howcroft, Vera Demberg:
From OpenCCG to AI Planning: Detecting Infeasible Edges in Sentence Generation. COLING 2016: 1524-1534 - [c82]Daniel Gnad, Martin Wehrle, Jörg Hoffmann:
Decoupled Strong Stubborn Sets. IJCAI 2016: 3110-3116 - [c81]Álvaro Torralba, Daniel Gnad, Patrick Dubbert, Jörg Hoffmann:
On State-Dominance Criteria in Fork-Decoupled Search. IJCAI 2016: 3265-3271 - [c80]Daniel Gnad, Marcel Steinmetz, Mathäus Jany, Jörg Hoffmann, Ivan Serina, Alfonso Gerevini:
Partial Delete Relaxation, Unchained: On Intractable Red-Black Planning and Its Applications. SOCS 2016: 45-53 - 2015
- [j29]Carmel Domshlak, Jörg Hoffmann, Michael Katz:
Red-black planning: A new systematic approach to partial delete relaxation. Artif. Intell. 221: 73-114 (2015) - [c79]Daniel Gnad, Jörg Hoffmann:
Beating LM-Cut with hmax (Sometimes): Fork-Decoupled State Space Search. ICAPS 2015: 88-96 - [c78]Jörg Hoffmann, Maximilian Fickert:
Explicit Conjunctions without Compilation: Computing hFF(PiC) in Polynomial Time. ICAPS 2015: 115-119 - [c77]Jörg Hoffmann, Alan Fern:
Journal Track Paper Abstracts. ICAPS 2015: 357-358 - [c76]Jörg Hoffmann:
Simulated Penetration Testing: From "Dijkstra" to "Turing Test++". ICAPS 2015: 364-372 - [c75]Álvaro Torralba, Jörg Hoffmann:
Simulation-Based Admissible Dominance Pruning. IJCAI 2015: 1689-1695 - [c74]Michael Backes, Fabian Bendun, Jörg Hoffmann, Ninja Marnau:
PriCL: Creating a Precedent, a Framework for Reasoning about Privacy Case Law. POST 2015: 344-363 - [c73]Daniel Gnad, Jörg Hoffmann:
Red-Black Planning: A New Tractability Analysis and Heuristic Function. SOCS 2015: 44-52 - [c72]Daniel Gnad, Jörg Hoffmann, Carmel Domshlak:
From Fork Decoupling to Star-Topology Decoupling. SOCS 2015: 53-61 - [i15]Michael Backes, Fabian Bendun, Jörg Hoffmann, Ninja Marnau:
PriCL: Creating a Precedent A Framework for Reasoning about Privacy Case Law. CoRR abs/1501.03353 (2015) - 2014
- [j28]Malte Helmert, Patrik Haslum, Jörg Hoffmann, Raz Nissim:
Merge-and-Shrink Abstraction: A Method for Generating Lower Bounds in Factored State Spaces. J. ACM 61(3): 16:1-16:63 (2014) - [j27]Emil Ragip Keyder, Jörg Hoffmann, Patrik Haslum:
Improving Delete Relaxation Heuristics Through Explicitly Represented Conjunctions. J. Artif. Intell. Res. 50: 487-533 (2014) - [j26]Peter Kissmann, Jörg Hoffmann:
BDD Ordering Heuristics for Classical Planning. J. Artif. Intell. Res. 51: 779-804 (2014) - [c71]Carlos Areces, Facundo Bustos, Martín Ariel Domínguez, Jörg Hoffmann:
Optimizing Planning Domains by Automatic Action Schema Splitting. ICAPS 2014 - [c70]Chris Fawcett, Mauro Vallati, Frank Hutter, Jörg Hoffmann, Holger H. Hoos, Kevin Leyton-Brown:
Improved Features for Runtime Prediction of Domain-Independent Planners. ICAPS 2014 - [c69]Jörg Hoffmann, Peter Kissmann, Álvaro Torralba:
"Distance"? Who Cares? Tailoring Merge-and-Shrink Heuristics to Detect Unsolvability. ECAI 2014: 441-446 - [c68]Michal Krajnanský, Jörg Hoffmann, Olivier Buffet, Alan Fern:
Learning Pruning Rules for Heuristic Search Planning. ECAI 2014: 483-488 - [r1]Jörg Hoffmann, Ingo Weber:
Web Service Composition. Encyclopedia of Social Network Analysis and Mining 2014: 2389-2399 - [i14]