Hector Geffner

About Hector Geffner

Hector Geffner, With an exceptional h-index of 53 and a recent h-index of 32 (since 2020), a distinguished researcher at Universidad Pompeu Fabra, specializes in the field of Artificial Intelligence, Automated Planning, Machine Learning, Cognitive Science.

His recent articles reflect a diverse array of research interests and contributions to the field:

Learning Generalized Policies for Fully Observable Non-Deterministic Planning Domains

On Policy Reuse: An Expressive Language for Representing and Executing General Policies that Call Other Policies

Combined Task and Motion Planning Via Sketch Decompositions (Extended Version with Supplementary Material)

Learning General Policies for Classical Planning Domains: Getting Beyond C

General and Reusable Indexical Policies and Sketches

General policies, subgoal structure, and planning width

Learning hierarchical policies by iteratively reducing the width of sketch rules

Learning General Policies with Policy Gradient Methods

Hector Geffner Information

University

Position

ICREA & Artificial Intelligence and Machine Learning Group DTIC

Citations(all)

12553

Citations(since 2020)

3648

Cited By

10355

hIndex(all)

53

hIndex(since 2020)

32

i10Index(all)

126

i10Index(since 2020)

80

Email

University Profile Page

Google Scholar

Hector Geffner Skills & Research Interests

Artificial Intelligence

Automated Planning

Machine Learning

Cognitive Science

Top articles of Hector Geffner

Learning Generalized Policies for Fully Observable Non-Deterministic Planning Domains

arXiv preprint arXiv:2404.02499

2024/4/3

Hector Geffner
Hector Geffner

H-Index: 33

On Policy Reuse: An Expressive Language for Representing and Executing General Policies that Call Other Policies

arXiv preprint arXiv:2403.16824

2024/3/25

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

Combined Task and Motion Planning Via Sketch Decompositions (Extended Version with Supplementary Material)

2023

Learning General Policies for Classical Planning Domains: Getting Beyond C

arXiv preprint arXiv:2403.11734

2024/3/18

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

General and Reusable Indexical Policies and Sketches

2023/12/4

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

General policies, subgoal structure, and planning width

arXiv preprint arXiv:2311.05490

2023/11/9

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

Learning hierarchical policies by iteratively reducing the width of sketch rules

2023/7/9

Jendrik Seipp
Jendrik Seipp

H-Index: 13

Hector Geffner
Hector Geffner

H-Index: 33

Learning General Policies with Policy Gradient Methods

2023

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

Learning generalized policies without supervision using gnns

arXiv preprint arXiv:2205.06002

2022/5/12

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

Learning First-Order Symbolic Planning Representations That Are Grounded

arXiv preprint arXiv:2204.11902

2022/4/25

Probabilistic and Causal Inference: The Works of Judea Pearl

2022/2/28

Hector Geffner
Hector Geffner

H-Index: 33

Rina Dechter
Rina Dechter

H-Index: 26

Language-based causal representation learning

arXiv preprint arXiv:2207.05259

2022/7/12

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

Target languages (vs. inductive biases) for learning to act and plan

Proceedings of the AAAI Conference on Artificial Intelligence

2022/6/28

Hector Geffner
Hector Geffner

H-Index: 33

FOND Planning with Explicit Fairness Assumptions

Journal of Artificial Intelligence Research

2022/6/23

Learning sketches for decomposing planning problems into subproblems of bounded width

arXiv preprint arXiv:2203.14852

2022/3/28

Jendrik Seipp
Jendrik Seipp

H-Index: 13

Hector Geffner
Hector Geffner

H-Index: 33

Learning general optimal policies with graph neural networks: Expressive power, transparency, and limits

Proceedings of the International Conference on Automated Planning and Scheduling

2022/6/13

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

Learning first-order representations for planning from black-box states: New results

arXiv preprint arXiv:2105.10830

2021/5/23

Learning general planning policies from small examples without supervision

Proceedings of the AAAI Conference on Artificial Intelligence

2021/5/18

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

General policies, representations, and planning width

Proceedings of the AAAI Conference on Artificial Intelligence

2021/5/18

Blai Bonet
Blai Bonet

H-Index: 22

Hector Geffner
Hector Geffner

H-Index: 33

Flexible FOND planning with explicit fairness assumptions

Proceedings of the International Conference on Automated Planning and Scheduling

2021/5/17

See List of Professors in Hector Geffner University(Universidad Pompeu Fabra)

Co-Authors

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