From Data-based to Model-based AI: Representation Learning for Planning

Project Information

RLeap

Grant agreement ID: 885107

DOI 10.3030/885107

EC signature date 24 April 2020

Start date 1 October 2020

End date 30 September 2025

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost € 2 498 625,00

EU contribution € 2 498 625,00

Coordinated by

RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN
Germany

Deliverables

Open Research Data Pilot (1)

Data Management Plan (DMP).

The Open Research Data Pilot will be prepared and submitted to the European Commission.

Publications

Peer reviewed articles (1)

FOND planning with explicit fairness assumptions

Author(s): Rodriguez, Ivan D.; Bonet, Blai; Sardina, Sebastian; Geffner, Hector
Published in: Journal of Artificial Intelligence Research, Issue 4, 2022, ISSN 1076-9757
Publisher: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.1.13599

Conference proceedings (12)

Learning Generalized Policies Without Supervision Using GNNs

Author(s): Simon Stählberg, Blai Bonet, Hector Geffner
Published in: Proc. Int. Conf. on Principles of Knowledge Representation and Reasoning (KR), 2022
Publisher: IJCAI Organization

General Policies, Serializations, and Planning Width

Author(s): Bonet, Blai; Geffner, Hector
Published in: Proceedings AAAI, 2021
Publisher: AAAI Press

Expressing and Exploiting the Common Subgoal Structure of Classical Planning Domains Using Sketches.

Author(s): Dominik Drexler, Jendrik Seipp, Hector Geffner
Published in: Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021
Publisher: IJCAI Organization

Online Action Recognition

Author(s): Suárez Hernández, Alejandro; Segovia Aguas, Javier; Torras, Carme; Alenyà Ribas, Guillem
Published in: Proc. National Conf. on Artificial Intelligence (AAAI), 2021
Publisher: AAAI Press

Learning first-order symbolic planning representations that are grounded

Author(s): Andres Occhipinti, Blai Bonet, Hector Geffner
Published in: Proc. ICAPS Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning, 2022
Publisher: AAAI Press
DOI: 10.48550/arxiv.2204.11902

Learning Sketches for Decomposing Planning Problems into Subproblems of Bounded Width

Author(s): Dominik Drexler, Jendrik Seipp, Hector Geffner
Published in: Proc. Int. Conf. on Planning and Scheduling (ICAPS), 2022
Publisher: AAAI Press

Learning General Policies from Small Examples Without Supervision

Author(s): Francès, Guillem; Bonet, Blai; Geffner, Hector
Published in: Proceedings AAAI, 2021
Publisher: AAAI Press

Learning First-Order Representations for Planning from Black Box States: New Results

Author(s): Ivan D. Rodriguez; Blai Bonet; Javier Romero; Hector Geffner
Published in: Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021
Publisher: IJCAI Organization
DOI: 10.24963/kr.2021/51

Generalized Planning as Heuristic Search

Author(s): Segovia-Aguas, Javier; Jiménez, Sergio; Jonsson, Anders
Published in: Proc. Int. Conf. on Planning and Scheduling (ICAPS), 2021
Publisher: AAAI Press

Flexible FOND Planning with Explicit Fairness Assumptions

Author(s): Rodriguez, Ivan D.; Bonet, Blai; Sardina, Sebastian; Geffner, Hector
Published in: Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, 2021
Publisher: AAAI Press

Target Languages (vs. Inductive Biases) for Learning to Act and Plan

Author(s): Geffner, Hector
Published in: Proceedings AAAI, 2022
Publisher: AAAI Press

Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limits

Author(s): Ståhlberg, Simon; Bonet, Blai; Geffner, Hector
Published in: Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, 2022
Publisher: AAAI Press

Monographic books (1)

Probabilistic and Causal Inference: The Works of Judea Pearl

Author(s): Hector Geffner, Rina Dechter, Joseph Y. Halpern (Editors)
Published in: 2022
Publisher: ACM Books
DOI: 10.1145/3501714