Hector Geffner
I am a researcher at the Institució
Catalana de Recerca i Estudis Avançats (ICREA) and a
professor at the Departament
de
Tecnologies de la Informació i les Comunicacions (DTIC),
Universitat Pompeu Fabra, in the
Artificial Intelligence Group.
I'm also a Wallenberg
Guest Professor at Linköping
University, Sweden.
My address is:
Hector Geffner
DTIC, Universitat Pompeu Fabra
C/Roc Boronat 138, Office 55.213
E-08018 Barcelona, Spain
- +34 93 542 2563 (voice)
+34 93 542 2451 (fax)
- firstname.lastname@upf.edu
Software
- Software and example files for each of the papers should be
available from co-author pages; if not, feel free to request
them by email
Opportunities
Papers, Talks, Slides, Books
- Learning
Generalized Policies Without Supervision Using GNNs. S
Stählberg, B Bonet, H Geffner. KR 2022
- Learning
First-Order Symbolic Planning Representations That Are
Grounded. A Occhipinti, B Bonet, H Geffner. ICAPS PRL
Workshop, 2022.
- Target Languages
(vs. Inductive Biases) for Learning to Act and Plan. H
Geffner. AAAI 2022 (Slides)
- Learning Sketches
for Decomposing Planning Problems into Subproblems of Bounded
Width. D Drexler, J Seipp, H Geffner. ICAPS 2022
- Learning General
Optimal Policies with Graph Neural Networks. S Stählberg,
B Bonet, H Geffner. ICAPS 2022
- Probabilistic
and Causal Inference: The Works of Judea Pearl. H.
Geffner. R. Dechter. Joseph Y. Halpern (Eds). ACM Books, 2022.
- Video: Target Languages for
Learning to Act & Plan. H. Geffner. IJCLR 2021
(Invited). (Slides)
- Learning
First-Order Representations for Planning from Black-Box
States: New Results. Iván D. Rodriguez, B
Bonet, J Romero, H Geffner. KR 2021
- Expressing and
Exploiting the Common Subgoal Structure of Classical Planning
Domains Using Sketches. D Drexler, J Seipp, H
Geffner. KR 2021
-
Flexible FOND
Planning with Explicit Fairness Assumptions. Iván D.
Rodriguez, B Bonet, S Sardiña, H Geffner. ICAPS 2021.
- General
Policies, Representations, and Planning Width. B Bonet, H
Geffner. AAAI 2021.
- Learning
General Planning Policies from Small Examples Without
Supervision. G Francès, B Bonet, H Geffner. AAAI 2021.
- Video: Model-free,
model-based, and general intelligence. H. Geffner. MIT
Embodied Intelligence Seminar, 4/2020.
- High-Level
Programming via Generalized Planning and LTL Synthesis. B
Bonet, G De Giacomo, H Geffner, F Patrizi, S Rubin. KR
2020
- Learning
First-Order Symbolic Representations for Planning from the
Structure of the State Space, B. Bonet, H. Geffner.
ECAI-2020
- Qualitative
Numeric Planning: Reductions and Complexity B Blai, H
Geffner. Journal of Artificial Intelligence Research, 2020
- From
data-based to model-based AI: Representation learning for
planning (RLeap). H. Geffner. Edited ERC Proposal,
8/2019. (Short
Version).
- Learning Features
and Abstract Actions for Computing Generalized Plans, B.
Bonet, G. Frances, H. Geffner. Proc. AAAI-2019
- Features,
Projections, and Representation Change for Generalized
Planning. B. Bonet, H. Geffner. Proc. IJCAI 2018
- Compact
Policies for Fully-Observable Non-Deterministic Planning as
SAT. T. Geffner, H. Geffner. Proc. ICAPS 2018 (Software)
- Planning
with pixels in (almost) real time.W. Bandres, B. Bonet, H.
Geffner. Proc. AAAI 2018
- Video:
Model-free,
Model-based, and General Intelligence. H.
Geffner. Proc. IJCAI 2018 (Invited). Slides.
Video.
- Purely
Declarative Action Descriptions are Overrated: Classical
Planning with Simulators. G. Frances, M. Ramirez, N.
Lipovetzky, H. Geffner. Proc. IJCAI 2017
- Generalized
Planning: Non-Deterministic Abstractions and Trajectory
Constraints. B. Bonet, G. De Giacomo, H. Geffner, S.
Rubin. Proc. IJCAI 2017
- A
Polynomial Planning Algorithm that Beats LAMA and FF. N
Lipovetzky, H Geffner. Proc. ICAPS 2017
- Multiagent
Online Planning with Nested Beliefs and Dialogue. F.
Kominis,and H. Geffner, Proc. ICAPS 2017.
- Best-First
Width Search: Exploration and Exploitation in Classical
Planning. N Lipovetzky, H Geffner. Proc. AAAI 2017
- Artificial
Intelligence and the Common Good (Slides). H. Geffner.
B-Debate AI: Dreams, Risks, and Reality. CosmoCaixa, Barcelona
2017
- Combined Task and
Motion Planning as Classical AI Planning. J.
Ferrer-Mestres, G. Frances, H. Geffner. 2016
- Traps,
invariants, and dead-ends. N Lipovetzky, C Muise, H
Geffner. Proc. ICAPS 2016
- E-STRIPS:
Existential Quantification in Planning and Constraint
Satisfaction. G Frances, H Geffner. Proc. IJCAI 2016
- Effective
Planning with More Expressive Languages. G Frances, H
Geffner. Proc. IJCAI 2016
- Factored
Probabilistic Belief Tracking. B Bonet, H Geffner. Proc.
IJCAI 2016
- Video: General
Solvers for General Artificial Intelligence. H. Geffner,
UPF 6/2016
- Planning
with State Constraints and its Application to Combined Task
and Motion Planning. J. Ferrer-Mestres, G. Frances, H.
Geffner 2015 ICAPS PlanRob Workshop
- Policies
that
Generalize: Solving Many planning Problems with the Same
Policy. B. Bonet and H. Geffner. Proc. IJCAI-2015
- Classical
Planning
with Simulators: Results on the Atari Video Games. N.
Lipovetzky, M. Ramirez, H. Geffner. Proc. IJCAI-2015
- Modeling
and
Computation in Planning: Better Heuristics for More Expressive
Languages. G. Frances and H. Geffner. Proc. ICAPS-2015
- Beliefs
in
Multiagent Planning: From One Agent to Many. F. Kominis
and H. Geffner. Proc. ICAPS-2015
- Video: Present
and Future of Artificial Intelligence (in Spanish). H.
Geffner, CCCB 12/2015
- Belief
Tracking
for Planning with Sensing: Width, Complexity, and
Approximations. B. Bonet and H. Geffner. JAIR 2014.
- Width-based
Algorithms
for Classical Planning: New Results. N. Lipovetzky and H.
Geffner. Proc. ECAI-2014
- Flexible
and
Scalable Partially Observable Planning with Linear
Translations. B. Bonet and H. Geffner. Proc. AAAI-2014
- Non-classical
Planning
wth a Classical Planner: The Power of Transformations. H.
Geffner. Proc. JELIA-2014. Springer.
- Artificial
Intelligence:
From
Programs
to
Solvers. H. Geffner. AI Communications. 2014
- Book: A Concise
Introduction to Models and Methods for Automated Planning.
H. Geffner and B. Bonet. Morgan & Claypool, 2013 (fragment,
slides).
- Computational
Models of Planning. H. Geffner. Wiley
Interdisciplinary Reviews: Cognitive Science, 2013
- Causal
Belief
Decomposition
for
Planning
with Sensing: Completeness Results and Practical Approximation.
B. Bonet and H. Geffner. Proc. IJCAI-2013, Beijing.
- Fair
LTL
Synthesis
for
Non-Deterministic
Systems using Strong Cyclic Planners. F. Patrizi, N.
Lipovetzky, H. Geffner. Proc. IJCAI-2013, Beijing.
- Width
and
Serialization
of
Classical
Planning
Problems. N. Lipovetzky and H. Geffner. Proc. ECAI-2012,
Montpellier. (Slides)
- Action
Selection
for
MDPs:
Anytime
AO*
vs. UCT. B. Bonet and H. Geffner. Proc. AAAI-2012,
Toronto.
- Width
and
Complexity
of
Belief
Tracking
in Non-Deterministic Conformant and Contingent Planning.
B. Bonet and H. Geffner. Proc. AAAI-2012.
- Planning
under Partial Observability by Classical Replanning: Theory
and Experiments. B. Bonet and H. Geffner. Proc.
IJCAI-2011, Barcelona
- Goal
Recognition over POMDPs: Inferring the Intention of a POMDP
Agent. M. Ramirez and H. Geffner. Proc. IJCAI-2011,
Barcelona
- Computing
Infinite Plans for LTL Goals using a Classical Planner. F.
Patrizi, N. Lipovetzky, G. De Giacomo, H. Geffner. Proc
IJCAI-2011, Barcelona
- Advanced
Introduction to Planning: Models and Methods, H. Geffner.
Tutorial at IJCAI-2011, Barcelona
- Qualitative
Numeric Planning. S. Srivastava, S. Zilberstein, N.
Immerman, H. Geffner. Proc. AAAI-2011, San Francisco
- Effective
Heuristics and Belief Tracking for Planning with Incomplete
Information. A. Albore, M. Ramirez, H. Geffner. Proc.
ICAPS-2011, Freiburg
- Searching
for Plans with Carefully Designed Probes. N. Lipovetzky
and H. Geffner. Proc. ICAPS-2011, Freiburg
- Heuristic
Search for Generalized Stochastic Shortest Path MDPs. A.
Kolobov, Mausam, D. Weld, H. Geffner, Proc. ICAPS-2011, Freiburg
- Planning
and Plan Recognition (Slides), Invited talk, Dagstuhl Plan
Recognition Seminar, 2011
- Heuristics
with Choice Variables: Bridging the Gap between Planning and
Graphical Models, E. Keyder, M. Ramirez, H. Geffner. ICAPS
Workshop 2011
- Course
on Automated Planning (Slides). Univ. La Sapienza, Rome,
Summer 2010
- The
Model-based Approach to Autonomous Behavior: Prospects and
Challenges (Slides), Invited talk, AI*IA, Brescia, 12/2010
- Heuristics,
Probability and Causality: A Tribute to Judea Pearl. R.
Dechter, H. Geffner, J. Halpern (Eds). College Publications,
2010 (Table
of
Contents)
- Heuristics,
Planning, and Cognition. In Heuristics,
Probability and Causality: A Tribute to Judea Pearl. R.
Dechter, H. Geffner, J. Halpern (Eds), College Publications,
2010.
- Probabilistic
Plan Recognition using off-the-shelf Classical Planners.
M. Ramirez and H. Geffner. Proc. AAAI-10. Atlanta, USA. 7/2010
- The
Model-based
Approach to Autonomous Behavior: A Personal View. H.
Geffner. Proc. AAAI-10. Atlanta, USA. 7/2010
- Automatic
Derivation of Finite-State Machines for Behavior Control.
B. Bonet, H. Palacios. H. Geffner. Proc. AAAI-10. Atlanta, USA.
7/2010
- Compiling
Away Uncertainty in Non-Deterministic Conformant Planning
Problems. A. Albore, H. Palacios, H. Geffner. Proc.
ECAI-10, Lisbon, Portugal, 8/2010
- Soft Goals
Can Be Compiled Away. E. Keyder and H. Geffner. Journal of
Artificial Intelligence Research, Volume 36, pages 547-556,
2009.
- Inference
and Learning in Planning (Extended Abstract). H. Geffner.
Proc. Discovery
Science 2009, Porto, Portugal, 10/2009.
- Automatic
Derivation
of
Memoryless
Policies
and
Finite-State
Controllers
Using
Classical
Planners.
B. Bonet, H. Palacios, H. Geffner. Proc. ICAPS-09.
- Inference
and
Decomposition
in
Planning
Using
Causal
Consistent
Chains.
N. Lipovetzky and H. Geffner. Proc. ICAPS-09.
- Plan
Recognition
as
Planning.
M. Ramirez and H. Geffner. Proc. IJCAI-09. Pasadena, USA.
7/09.
- A
Translation-based Approach to Contingent Planning. A.
Albore, H. Palacios, H. Geffner. Proc. IJCAI-09. Pasadena, USA.
7/09.
- Trees
of
Shortest
Paths
vs.
Steiner
Trees:
Understanding
and
Improving
Delete
Relaxation
Heuristics.
E. Keyder and H. Geffner. Proc. IJCAI-09.
- Solving
POMDPs:
RTDP-Bel
vs.
Point-based
Algorithms.
B. Bonet and H. Geffner. Proc. IJCAI-09.
- Compiling
Uncertainty
Away
in
Conformant
Planning
Problems
with
Bounded
Width.
H. Palacios and H. Geffner Journal of AI Research (JAIR).
2009.
- Heuristics
for Planning with Penalties and Rewards Formulated in Logic
and Computed Through Circuits, B. Bonet and H. Geffner.
Artificial Intelligence, 2008 (172) 1579-1604
- Heuristics
for Planning with Action Costs Revisited. E. Keyder and H.
Geffner. Proc. ECAI-08.
- Unifying
the Causal Graph and Additive Heuristics, M. Helmert and
H. Geffner, Proc. ICAPS 2008.
- AI
at
50:
From Programs to Solvers. Models and Techniques for General
Intelligence (Slides). H. Geffner. University of
Edinburgh, School of Informatics. Distinguished Lecture Series.
12/2007
- From
Conformant
into
Classical Planning: Efficient Translations that may be
Complete Too. H. Palacios and H. Geffner. Proc. ICAPS-2007
- Structural
Relaxations by Variable Renaming and their Compilation
for Solving MinCostSAT. M. Ramirez and H. Geffner.
Proc. CP-2007
- The
Causal Graph Heuristic is the Additive Heuristic plus Context.
H. Geffner. Proc. 2007 ICAPS HSDIP Workshop
- Fast
and Informed Action Selection for Planning with Sensing.
A. Albore, H. Palacios, H. Geffner. Proc. CAEPIA-07,
Springer
- Set-Additive
and TSP Heuristics for Planning with Action Costs and Soft
Goals. E. Keyder and H. Geffner. Proc. 2007 HSDIP
ICAPS
- Logical
Encodings
with No Time Indexes for Defining and Computing Admissible
Heuristics for Planning. M. Ramirez, B. Bonet, H. Geffner.
Proc. 2007 ICAPS Workshop.
- Heuristics
for Planning with Action Costs. E. Keyder and H. Geffner.
Proc. 12th Conf. Spanish AI (CAEPIA-07),
Springer.
- Compiling
Uncertainty Away: Solving Conformant Planning Problems Using a
Classical Planner (Sometimes). H. Palacios and H. Geffner.
Proc. AAAI-2006
- Heuristics
for Planning with Penalties and Rewards using Compiled
Knowledge. B. Bonet and H. Geffner. Proc. KR-2006
- Learning
Depth-First
Search:
A
Unified
Approach
to
Heuristic
Search
in
Deterministic
and
Non-Deterministic
Settings, and its application to MDPs. B. Bonet and H.
Geffner. Proc. ICAPS-2006
- Branching
and
Pruning:
An
Optimal
Temporal
POCL
Planner
based
on
Constraint
Programming
(Extended Version). V. Vidal and H. Geffner. Artificial
Intelligence, Vol 170(3), pp 298-335, March
2006.
- mGPT:
a
Probabilistic
Planner based on Heuristic Search. B. Bonet and H.
Geffner. Journal of AI Research, Vol 24, pp 933-944, 2005.
- Search
and Inference in AI Planning. H. Geffner. Proc. CP-2005
Invited talk (Slides)
- Mapping
Conformant Planning into SAT through Compilation and
Projection. H. Palacios and H. Geffner. Lecture
Notes in Computer Sciences, vol 4177. Proc.
CAEPIA-05 (originally in Spanish)
- Learning
in
Depth-First
Search:
A
Unified
Approach
to
Heuristic
Search
in
Deterministic,
Non-Deterministic,
Probabilistic,
and Game Tree Settings. B. Bonet and H. Geffner.
2005.
- Solving
Simple
Planning
Problems with More Inference and No Search, V. Vidal and
H. Geffner. Proc. CP-2005.
- Selecting
Actions and Making Decisions: Lessons from AI Planning. H.
Geffner. Proc. IJCAI-05 MNAS-2005 Workshop on Modeling Natural
Action Selection (MNAS-05). (Slides)
- An
Algorithm Better than AO*? B. Bonet and H. Geffner.
Proc. AAAI-2005 (Slides)
- New
Admissible Heuristics for Domain-Independent Planning. P.
Haslum, B. Bonet and H. Geffner. Proc. AAAI-05.
- Pruning
Conformant Plans by Counting Models on Compiled d-DNNF
Representations.H. Palacios, B. Bonet, A. Darwiche, H.
Geffner. Proc. ICAPS-2005.
- Learning
Generalized Policies from Planning Examples Using Concept
Languages (Extended and Revised Version). M. Martin
and H. Geffner, Applied Intelligence 20 (1) , 9-19, 2004
- Branching
and Pruning: An Optimal Temporal POCL Planner based on
Constraint Programming. V. Vidal and H. Geffner.
Proc. AAAI-04
- Planning
Graphs
and Knowledge Compilation. H. Geffner. Proc. KR-04.
(Slides)
- PDDL
2.1:
Representation
vs. Computation.H. Geffner (a commentary on PDDL 2.1 and
the 3rd Int. Planning Competition). J. of AI Research, vol 20,
2003.
- Faster
Heuristic
Search Algorithms for Planning with Uncertainty and Full
Feedback. B. Bonet and H. Geffner. Proc. IJCAI 2003
- Labeled
RTDP: Improving the Convergence of Real Time Dynamic
Programming. B. Bonet and H. Geffner. Proc. ICAPS-2003
- Branching
Matters: Alternative Branching in Graphplan. J. Hoffmann
and H. Geffner. Proc. ICAPS-2003
- Perspectives
on Artificial Intelligence Planning. H. Geffner Proc.
AAAI-2002. Invited talk (Slides)
- Planning
as Branch and Bound: A Constraint Programming
Implementation; H. Palacios and H. Geffner. XVIII
Latin-American Conf. on Informatics (CLEI-2002)
- Heuristic
Search
Planning:
Progress
and
Challenges
, Slides Invited Talk at European Conf. on Planning
(ECP-2001), (4
slides
per page)
- Planning
as Branch and Bound and its Relation to Constraint-based
Approaches; H. Geffner, 4/2001
- GPT:
A Tool for Planning with Uncertainty and Partial Information;
B. Bonet and H. Geffner; IJCAI-2001 Workshop on Planning
with Incomplete Info, 8/2001
- Planning
and Control in Artificial Intelligence: a Unifying
Perspective. B. Bonet and H. Geffner. Applied
Intelligence, Vol 14(3), 2001, pp 237--252.
- Heuristic
Planning with Time and Resources;
P. Haslum and H. Geffner, Proceedings ECP-2001
4/2001, Springer
- HSP2:
Description
HSP
Planner
in
AIPS-2000
Competition,
B.
Bonet
and
H.
Geffner,
AI
Magazine Vol 22 (3), 2001, pp 77--80
- Planning
as Heuristic Search B. Bonet and H. Geffner.
Artificial Intelligence, Special issue on Heuristic Search.
Vol 129 (1-2) 2001
- Planning
with
Incomplete
Information
as
Heuristic
Search
in
Belief
Space
B. Bonet and H. Geffner. Proc. AIPS-2000
- Admissible
Heuristics
for
Optimal
Planning
P. Haslum H. Geffner. Proc. AIPS-2000
- Learning
generalized
policies
in
planning
using
concept
languages
M. Martin and H. Geffner. Proc. KR-2000 (Slides)
- HSP:
Heuristic
Search
Planner
B. Bonet and H. Geffner. Entry at AIPS-98 Planning
Competition, AI Magazine Vol 21(2), 2000
- Functional
Strips:
a
more
flexible
language
for
planning
and
problem
solving
H. Geffner. In Logic-Based Artificial Intelligence, Jack
Minker (Ed.), Kluwer, 2000.
- Planning
as
Heuristic
Search:
New
Results
B. Bonet and H. Geffner. Proc. European Conference on
Planning (ECP-99), Springer. (Slides)
- Modelling
Intelligent
Behaviour:
the
Markov
Decision
Approach
H. Geffner. Invited talk IBERAMIA 1998, Lect. Notes in AI
1484, H. Coelho (Ed), Springer,
- Classical,
Probabilistic
and
Contingent
Planning:
Three
Models,
One
Algorithm
H. Geffner. Proceedings AIPS'98 Workshop on Planning as
Combinatorial Search. (Slides)
- High-Level
Planning
and
Control
with
Incomplete
Information
Using
POMDPs
H. Geffner and B. Bonet. Proceedings Fall AAAI Symposium
on Cognitive Robotics, 1998. (Slides)
- Solving
Large
POMDPs
by
Real
Time
Dynamic
Programming
H. Geffner and B. Bonet. Working Notes Fall AAAI Symposium
on POMDPS. 1998.
- Modeling
action,
knowledge
and
control
H. Geffner and J. Wainer. Proceedings European Conference
on Artificial Intelligence (ECAI-98), Brighton, UK. 8/98.
- Learning
Sorting
and
Decision
Trees
with
POMDPs
B. Bonet and H. Geffner. Proc ICML-98. (Slides)
- Causality,
Constraints
and
the
Side
Effects
of
Actions
H. Geffner. Proceedings IJCAI-97, Naogoya, Japan, 8/97.
- A
fast and robust action selection mechanism for planning B.
Bonet, G. Loerincs, H. Geffner. Proceedings AAAI-97. Provide,
RI, 7/97. (Slides)
- An
Analysis
of
control
programs
using
models
of
action.
J. Ramirez and H. Geffner. AAAI-97 Workshop on Action.
1997 (Slides)
Short Bio
Hector Geffner got his Ph.D at UCLA in 1989. He
then worked as Staff Research Member at the IBM T.J. Watson
Research Center in NY, USA and at the Universidad Simon Bolivar, in
Caracas, Venezuela. Since 2001, he is a researcher at ICREA and a professor at the Universitat Pompeu Fabra,
Barcelona, and since 2019, a Wallenberg
Guest Professor at Linköping
University, Sweden. Hector is a former Associate Editor of
Artificial
Intelligence and the Journal of Artificial
Intelligence Research, and a Fellow of AAAI and EurAI. He is the author of
the book Default Reasoning: Causal and Conditional Theories, MIT
Press, 1992, and "A
Concise Introduction to Models and Methods for Automated
Planning" with Blai Bonet, Morgan and Claypool, 2013.
He edited two books in tribute of Judea Pearl with Rina Dechter
and Joe
Halpern: "Heuristics,
Probability, and Causality: a Tribute to Judea Pearl",
College Publications, 2010, and Probabilistic
and Causal Inference: The Works of Judea Pearl, ACM Books
2022. Hector is interested in computational models of reasoning,
action, learning, and planning that are general and effective.
He is also a concerned citizen (particularly concerned these
days) and, aside from courses on logic and AI, he teaches a
course on social and technological change. He leads a project on
representation learning for acting and planning (RLeap),
funded by an Advanced ERC
grant, 2020-2025.