Vincent Vidal - homepage

Welcome…

I have been a research scientist at ONERA since september 2009, in the Systems Control and Flight Dynamics (DCSD) department, Control and Decision (CD) research unity. I was previously an associate professor at the Academic Institute of Technology of Lens (IUT de Lens), and a researcher at the Research Centre in Computer Science of Lens (CRIL), University of Artois. Prior to this I was an assistant professor at the University Paul Sabatier where I obtained a PhD in computer science at the Research Institute in Computer Science of Toulouse (IRIT).

My main research interests are Automated Planning in Artificial Intelligence, Heuristic Search and Constraint Programming.

News

Contact information

Vincent Vidal

ONERA — DCSD
2, avenue Edouard Belin
BP 74025
31055 TOULOUSE Cedex 4, FRANCE

email: Vincent.Vidal@onera.fr

phone: +33 (0)5 62 25 27 74

 ONERA

Valid XHTML 1.1 Valid CSS

Activities

Professional positions

sep. 2009 — …Research scientist, ONERA, Toulouse.
Department: Systems Control and Flight Dynamics (DCSD).
Research unity: Control and Decision (CD).
sep. 2003 — aug. 2009Associate professor, Academic Institute of Technology of Lens (IUT de Lens), University of Artois.
Research lab: Research Centre in Computer Science of Lens (CRIL).
sep. 1998 — jan. 2003Assistant professor, University Paul Sabatier, Toulouse.
Research lab: Research Institute in Computer Science of Toulouse (IRIT).

Education

1998 — 2001PhD in computer science (specialty Artificial Intelligence), University Paul Sabatier, Toulouse.
Title: “Recherche dans les graphes de planification, satisfiabilité et stratégies de moindre engagement—Les systèmes LCGP et LCDPP” (Search in planning graphs, satisfiability and least commitment strategies—The LCGP and LCDPP systems).
Research lab: Research Institute in Computer Science of Toulouse (IRIT).
Advisor: Michel Cayrol, assisted by Pierre Régnier.
1997 — 1998Master (specialty Knowledge Representation and Reasoning Formalization), University Paul Sabatier, Toulouse.
Research lab: Research Institute in Computer Science of Toulouse (IRIT).
Advisor: Pierre Régnier.

Awards

2011Winner of the Deterministic Temporal Satisficing Track with the DAEyahsp planner, 7th International Planning Competition (IPC-2011), Freiburg, Germany, June 2011.
2011Runner-up ex-aequo of the Deterministic Temporal Satisficing Track with the YAHSP2-MT planner, 7th International Planning Competition (IPC-2011), Freiburg, Germany, June 2011.
2010Silver Medal for the work about the DAEx planner at the 7th Annual Humies Awards for Human-Competitive Results Produced by Genetic and Evolutionnary Computation Held at the Genetic and Evolutionnary Computation Conference (HUMIES-2010), Portland, OR, USA, July 2010.
2006Distinguished performance for the CPT planner in Optimal Track (Temporal Domains), 5th International Planning Competition (IPC-2006), Ambleside, UK, June 2006.
20042nd place for the YAHSP planner in Suboptimal Propositional Track, 4th International Planning Competition (IPC-2004), Whistler, BC, Canada, June 2004.
20042nd place for the CPT planner in Optimal Track, 4th International Planning Competition (IPC-2004), Whistler, BC, Canada, June 2004.

Contracts & Grants

2009 — …Leader at the ONERA level of the DESCARWIN project funded by the French National Research Agency (ANR) under the COSINUS call.
Theme: “Evolutionary planning”, coordinated by Thales TRT.
Partners: INRIA/TAO, Onera, Thales TRT.
2006 — 2009Industrial contract with the Parisian Company of Urban Transportation (RATP).
Theme: “Recomposition and optimization of the timetable for public urban transportation regulation”.
2005 — 2009Leader of the PLANEVO project funded by the French National Research Agency (ANR) under the “Young Researchers” call.
Theme: “Planning under uncertainty in a dynamic environment”.
1998 — 2001Scolarship PhD grant from the French Ministry of Education, Research and Technology (“bourse MENRT”).

Students

2011 — …Simon Vernhes, PhD, “Planification distribuée” (Distributed Planning).
Co-directed with Guillaume Infantes (Onera, DCSD) and Éric Noulard (Onera, DTIM).
2003 — 2008Zied Loukil, PhD, “Intégration des ressources en planification temporelle optimale” (Resources integration in optimal temporal planning), defended on 12 december 2008.
Co-directed with Pierre Marquis (CRIL, University or Artois) and Abdelmajid Ben Hamadou (University of Sphax, Tunisia).
Zied is actually associate professor at University of Sfax, Tunisia.
2005 — 2007Sébastien Tabary, PhD, “Les conflits en programmation par contraintes—Application à la planification” (Conflicts in Constraint Programming—application to Planning), defended on 22 november 2007.
Co-directed with Christophe Lecoutre and Lakhdar Saïs (CRIL, University or Artois).
Sébastien is actually associate professor at University of Artois.
2005Sébastien Tabary, Master, “Pondération des heuristiques pour une approche de la planification en programmation par contraintes” (Weighted heuristics for a constraint programming approach).
Co-directed with Christophe Lecoutre and Lakhdar Saïs (CRIL, University or Artois).
2004Élise Bonzon, Master, “Planification par recherche heuristique dans les espaces d'états” (Planning by heuristic search in the space of states).
Co-directed with Pierre Régnier (IRIT, University Paul Sabatier).
2003Zied Loukil, Master, “Planification dans l'incertain avec observabilité nulle : Approche par compilation” (Planning under uncertainty with no observability: and approach by compilation).
Co-directed with Pierre Marquis (CRIL, University of Artois).
2002Frédéric Maris, Master, “Traduction et étude comparative de codages SAT pour la planification” (Compilation and comparative study of SAT encodings of planning).
Co-directed with Pierre Régnier (IRIT, University Paul Sabatier).
2002Marjorie Couzinier, Master, “Prise en compte des interactions dans les espaces d'états pour l'amélioration de la recherche heuristique” (Interaction handling in state space for improving heuristic search).
Co-directed with Pierre Régnier (IRIT, University Paul Sabatier).

Committees

  • Program committees:
    • 23rd International Joint Conference on Artificial Intelligence (IJCAI-2013), Beijing, China, August 2013.
    • 23rd International Conference on Automated Planning and Scheduling (ICAPS-2013), Rome, Italy, June 2013.
    • 8th International Workshop on Constraint Reasoning, Planning and Scheduling Problems for a Sustainable Future (GREEN-COPLAS-2013), Beijing, China, June 2013.
    • 11th ICAPS Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS-2013), Rome, Italy, June 2013.
    • 11st ICAPS Workshop on Evolutionary Techniques in Planning and Scheduling (EVOPS-2013), Rome, Italy, June 2013.
    • 8èmes Journées Francophones Planification, Décision, Apprentissage pour la conduite de systèmes (JFPDA-2013), Lille, France, July 2013.
    • 7èmes Journées de l'Intelligence Artificielle Fondamentale (JIAF-2013), Aix-en-Provence, France, June 2013.
    • 22nd International Conference on Automated Planning and Scheduling (ICAPS-2012), Atibaia, Sao Paulo, Brazil, June 2012.
    • 5th Symposium on Combinatorial Search (SOCS-2012), Niagara Falls, Canada, July 2012.
    • 5th Symposium of the Many-core Applications Research Community (MARC-2012), Toulouse, France, July 2012.
    • 7th ICAPS Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS-2012), Atibaia, Brazil, June 2012.
    • 7èmes Journées Francophones Planification, Décision, Apprentissage pour la conduite de systèmes (JFPDA-2012), Nancy, France, May 2012.
    • 6èmes Journées de l'Intelligence Artificielle Fondamentale (JIAF-2012), Toulouse, France, May 2012.
    • 4th Symposium on Combinatorial Search (SOCS-2011), Cardona, Spain, July 2011.
    • 25th AAAI Conference on Artificial Intelligence (AAAI-2011), San Francisco, CA, USA, August 2011.
    • 21st International Conference on Automated Planning and Scheduling (ICAPS-2011), Freiburg, Germany, June 2011.
    • 22nd International Joint Conference on Artificial Intelligence (IJCAI-2011), Barcelona, Spain, July 2011.
    • 6th ICAPS Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS-2011), Freiburg, Germany, June 2011.
    • 3rd ICAPS Workshop on Heuristics for Domain-independent Planning (HDIP-2011), Freiburg, Germany, June 2011.
    • 5èmes Journées de l'Intelligence Artificielle Fondamentale (JIAF-2011), Lyon, France, June 2011.
    • 22nd International Conference on Tools with Artificial Intelligence (ICTAI-2010), Arras, France, October 2010.
    • 19th European Conference on Artificial Intelligence (ECAI-2010), Lisbon, Portugal, August 2010.
    • 24th AAAI Conference on Artificial Intelligence (AAAI-2010), Atlanta, GA, USA, July 2010.
    • 20th International Conference on Automated Planning and Scheduling (ICAPS-2010), Toronto, ON, Canada, May 2010.
    • 5th ICAPS Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS-2010), Toronto, ON, Canada, May 2010.
    • 17ème Congrès francophone AFRIF-AFIA de Reconnaissance des Formes et Intelligence Artificielle (RFIA-2010), Caen, France, January 2010.
    • 5èmes Journées Francophones Planification, Décision, Apprentissage pour la conduite de systèmes (JFPDA-2010), Besançon, France, June 2010.
    • 4th ICAPS Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS-2009), Thessaloniki, Greece, September 2009.
    • 18th European Conference on Artificial Intelligence (ECAI-2008), Patras, Greece, July 2008.
    • 3èmes Journées Francophones Planification, Décision, Apprentissage pour la conduite de systèmes (JFPDA-2008), Metz, France, June 2008.
    • 16ème Congrès francophone AFRIF-AFIA de Reconnaissance des Formes et Intelligence Artificielle (RFIA-2008), Amiens, France, January 2008.
    • 3èmes Journées Francophones Planification, Décision, Apprentissage pour la conduite de systèmes (JFPDA-2008), Metz, France, June 2008.
    • 1st ICAPS Workshop on Heuristics for Domain-independent Planning (HDIP-2007), Providence, RI, USA, September 2007.
    • 2nd ICAPS Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS-2007), Providence, RI, USA, September 2007.
    • 2èmes Journées Francophones Planification, Décision, Apprentissage pour la conduite de systèmes (JFPDA-2007), Grenoble, France, July 2007.
    • 17th European Conference on Artificial Intelligence (ECAI-2006), Riva del Garda, Italy, August 2006.
    • 1st ICAPS Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS-2006), Cumbria, UK, June 2006.
    • 1ères Journées Francophones Planification, Décision, Apprentissage pour la conduite de systèmes (JFPDA-2006), Toulouse, France, May 2006.
    • 2èmes Journées Francophones de Programmation par Contraintes (JFPC-2006), Nîmes, France, June 2006.
    • IJCAI-2005 Workshop on Planning and Learning in A Priori Unknown or Dynamic Domains (link), Edinburgh, UK, August 2005.
    • 1ères Journées Francophones de Programmation par Contraintes (JFPC-2005), Lens, France, June 2005.
    • 7èmes Rencontres des Jeunes Chercheurs en Intelligence Artificielle (RJCIA-2005), Nice, France, May 2005.
  • Journal reviewing:
  • Conference reviewing:
    • 20th International Joint Conference on Artificial Intelligence (IJCAI-2007), Hyderabad, India, January 2007.
    • 5th Mexican International Conference on Artificial Intelligence (MICAI-2006), Apizaco, Mexico, November 2006.
    • 20th AAAI Conference on Artificial Intelligence (AAAI-2005), Pittsburgh, PA, USA, July 2005.
    • 19th International Joint Conference on Artificial Intelligence (IJCAI-2005), Edinburgh, UK, July 2005.
    • 16th European Conference on Artificial Intelligence (ECAI-2004), Valencia, Spain, August 2004.
    • 14ème Congrès francophone AFRIF-AFIA de Reconnaissance des Formes et Intelligence Artificielle (RFIA-2004), Toulouse, France, January 2004.
    • 18th International Joint Conference on Artificial Intelligence (IJCAI-2003), Acapulco, Mexico, August 2003.
    • 6èmes Rencontres des Jeunes Chercheurs en Intelligence Artificielle (RJCIA-2003), Laval, France, July 2003.
    • 6th International Conference on AI Planning and Scheduling (AIPS-2002), Toulouse, France, April 2002.
    • 6th European Conference on Planning (ECP-2001), Toledo, Spain, September 2001.
  • Organizing committees:
    • 5th Symposium of the Many-core Applications Research Community (MARC-2012), Toulouse, France, July 2012.
    • 1ères Journées Francophones de Programmation par Contraintes (JFPC-2005), Lens, France, June 2005.
    • 9th International Workshop on Non-Monotonic Reasoning (NMR-2002), Toulouse, France, April 2002.
    • 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU-2001), Toulouse, France, September 2001.
  • National specialist commitees:
    • 2009: Elected member of the Recruitment Commitee (Computer Science section 27), University of Artois.
    • 2009: External member of the Recruitment Commitee (Computer Science section 27), University of Lille I.
    • 2004-2009: External member of the Recruitment Commitee (Computer Science section 27), University of Provence.
    • 2005-2008: External member of the Recruitment Commitee (Computer Science section 27), University of Angers.

CPT

Description

This is a joint work with Héctor Geffner.

CPT (which stands for “Constraint Programming Temporal planner”) is a planning system for optimal temporal STRIPS planning. It combines a branching scheme based on Partial Order Causal Link (POCL) Planning with powerful and sound pruning rules implemented as constraints.

The development of CPT is motivated by the limitation of heuristic state approaches to parallel and temporal planning that suffer from a high branching factor (cf. HSP* family of planners) and thus have difficulties matching the performance of planners built on SAT techniques such as SATPLAN. In CPT, all branching decisions (resolution of open supports, support threats, and mutex threats), generate binary splits, and nodes in the search correspond to “partial plans” very much as in POCL planning.

The CPT planner is implemented using the Choco CP library that operates on top of Claire, a high-level programming language that compiles into C++. Further details can be found in the AAAI-2004 paper that is concerned mostly with the computation of optimal canonical plans; plans where no ground action is done more than once. The version of CPT on this page removes this restriction, and computes optimal temporal plans, whether canonical or not. Currently, the semantics of these plans follows the one in (Smith and Weld, IJCAI-99) where interfering actions are not allowed to overlap in time. This condition has been relaxed in PDDL 2.1 where interfering actions may overlap sometimes (e.g., when preconditions do not have to be preserved throughout the execution of the action).

Papers

This work has been published at the AAAI-2004 conference, at the Workshop on “Integrating Planning Into Scheduling” WIPIS-2004 held in conjunction with ICAPS-2004 [ps] [ps.gz] [pdf] and in the Artificial Intelligence Journal [ps] [ps.gz] [pdf]. It is also published in the french conference JNPC-2004 [ps] [ps.gz] [pdf].

Awards

Downloads

You can find here the source code and some binary versions of our planning system. The source package also contains the original source code of Claire required for the compilation of CPT, plus the tailored version of Choco that we use. It should compile on any platform where Claire can be compiled, that is at least Linux, Windows, Solaris...

YAHSP

Description

YAHSP (which stands for “Yet Another Heuristic Search Planner”) is a planning system for non-optimal STRIPS planning. It is based on recent ideas from the planning as heuristic search framework, initiated by the planners ASP and HSP from Blai Bonet and Hector Geffner.

The heuristic is computed in a way very similar to Jörg Hoffmann's FF planner, but used in different ways. We introduce a novel way for extracting information from the computation of the heuristic and for tackling with helpful actions, by considering the high quality of the plans computed by the heuristic function in numerous domains. For each evaluated state, we employ actions from these plans in order to find the beginning of a valid plan that can lead to a reachable state, that will often bring us closer to a solution state. The lookahead state thus calculated is then added to the list of nodes that can be chosen to be developed following the numerical value of the heuristic. We use this lookahead strategy in a complete best-first search algorithm, modified in order to take into account helpful actions by preferring nodes that can be developed with such actions over nodes that can be developed with actions not considered as helpful.

We provide below an empirical evaluation which demonstrates that in numerous planning benchmark domains, the performance of heuristic search planning and the size of the problems that can be handled have been drastically improved, while in more “difficult” domains these strategies remain interesting even if they sometimes degrade plan quality.

Papers

Here is a technical report describing the YAHSP planning system: [ps.gz] [pdf]. This work has also been published at the poster session of IJCAI-2003 [ps] [ps.gz] [pdf], at ICAPS-2004 [ps] [ps.gz] [pdf], and at the french conference RFIA-2004 [ps] [ps.gz] [pdf].

Award

Downloads

You can find here bytecode and binary versions of my planning system. Source code is not available yet.

Publications / Compact View

All publications

  1. HiPOP: Hierarchical Partial-Order Planning. P. Bechon, M. Barbier, C. Lesire-Cabaniols, G. Infantes, V. Vidal, STAIRS-2014, 2014.
  2. Divide-and-Evolve: the Marriage of Descartes and Darwin. J. Dréo, P. Savéant, M. Schoenauer, V. Vidal, IPC-2014, 2014.
  3. YAHSP3 and YAHSP3-MT in the 8th International Planning Competition. V. Vidal, IPC-2014, 2014.
  4. La planification en intelligence artificielle. R. Sabbadin, F. Teichteil-Königsbuch, V. Vidal, L'I.A. frontières et applications, 2014.
  5. Pareto-Based Multiobjective AI Planning. M. Khouadjia, M. Schoenauer, V. Vidal, J. Dréo, P. Savéant, IJCAI-2013, 2013.
  6. Problem Splitting using Heuristic Search in Landmark Orderings. S. Vernhes, G. Infantes, V. Vidal, IJCAI-2013, 2013.
  7. Multi-Objective AI Planning: Comparing Aggregation and Pareto Approaches. M. Khouadjia, M. Schoenauer, V. Vidal, J. Dréo, P. Savéant, EvoCOP-2013, 2013.
  8. Multi-Objective AI Planning: Evaluating DAEyahsp on a Tunable Benchmark. M. Khouadjia, M. Schoenauer, V. Vidal, J. Dréo, P. Savéant, EMO-2013, 2013.
  9. Quality Measures of Parameter Tuning for Aggregated Multi-Objective Temporal Planning. M. Khouadjia, M. Schoenauer, V. Vidal, J. Dréo, P. Savéant, LION-2013, 2013.
  10. Proceedings of the ICAPS-2013 Workshop on Evolutionary Techniques in Planning and Scheduling. Magali Barbier, Valentina Poggioni, Marc Schoenauer, Vincent Vidal (editors), 11st ICAPS Workshop on Evolutionary Techniques in Planning and Scheduling (EVOPS-2013), 2013.
  11. Pareto-Based Multiobjective AI Planning. M. Khouadjia, M. Schoenauer, V. Vidal, J. Dréo, P. Savéant, EVOPS-2013, 2013.
  12. Landmark-based Meta Best-First Search Algorithm: First Parallelization Attempt and Evaluation. S. Vernhes, G. Infantes, V. Vidal, HSDIP-2013, 2013.
  13. Synthesis of Plans or Policies for Controlling Dynamic Systems. G. Verfaillie, C. Pralet, V. Vidal, G. Infantes, C. Lesire-Cabaniols, Aerospace Lab Journal 4, 2012.
  14. The Landmark-based Meta Best-First Search Algorithm for Classical Planning. S. Vernhes, G. Infantes, V. Vidal, STAIRS-2012, 2012.
  15. Domain-Independent Relaxation Heuristics for Probabilistic Planning with Dead-ends. F. Teichteil-Königsbuch, V. Vidal, G. Infantes, HSDIP-2012, 2012.
  16. Parallel AI Planning on the SCC. V. Vidal, S. Vernhes, G. Infantes, MARC-2011, 2011.
  17. Extending Classical Planning Heuristics to Probabilistic Planning with Dead-ends. F. Teichteil-Königsbuch, V. Vidal, G. Infantes, AAAI-2011, 2011.
  18. Parallel Divide-and-Evolve: Experiments with OpenMP on a Multicore Machine. C. Candan, J. Dréo, P. Savéant, V. Vidal, GECCO-2011, 2011.
  19. YAHSP2: Keep It Simple, Stupid. V. Vidal, IPC-2011, 2011.
  20. Divide-and-Evolve: the Marriage of Descartes and Darwin. J. Dréo, P. Savéant, M. Schoenauer, V. Vidal, IPC-2011, 2011.
  21. CPT4: An Optimal Temporal Planner Lost in a Planning Competition without Optimal Temporal Track. V. Vidal, IPC-2011, 2011.
  22. Prise en compte d'un contexte évolutif dans la coordination des opérations de secours. F. Aligne, P. Savéant, V. Vidal, WISG-2011, 2011.
  23. Adaptive K-Parallel Best-First Search: A Simple but Efficient Algorithm for Multi-Core Domain-Independent Planning. V. Vidal, L. Bordeaux, Y. Hamadi, SOCS-2010, 2010.
  24. On the Generality of Parameter Tuning in Evolutionary Planning. J. Bibaï, P. Savéant, M. Schoenauer, V. Vidal, GECCO-2010, 2010.
  25. An Evolutionary Metaheuristic based on State Decomposition for Domain-Independent Satisficing Planning. J. Bibaï, P. Savéant, M. Schoenauer, V. Vidal, ICAPS-2010, 2010.
  26. On the Benefit of Sub-Optimality within the Divide-and-Evolve Scheme. J. Bibaï, P. Savéant, M. Schoenauer, V. Vidal, EvoCOP-2010, 2010.
  27. An Evolutionary Metaheuristic based on State Decomposition for Domain-Independent Satisficing Planning. J. Bibaï, P. Savéant, M. Schoenauer, V. Vidal, JFPDA-2010, 2010.
  28. Reasoning from Last Conflict(s) in Constraint Programming. C. Lecoutre, L. Saïs, S. Tabary, V. Vidal, Artificial Intelligence 173 (18), 2009.
  29. Learning Divide-and-Evolve Parameter Configurations with Racing. J. Bibaï, P. Savéant, M. Schoenauer, V. Vidal, ICAPS-2009 Workshop on Planning and Learning (link), 2009.
  30. Identification et exploitation d'états partiels. C. Lecoutre, S. Tabary, V. Vidal, JFPC-2009, 2009.
  31. Evolutionary State Decomposition for Temporal Planning. J. Bibaï, P. Savéant, M. Schoenauer, V. Vidal, JFPDA-2009, 2009.
  32. Divide-and-Evolve: a Sequential Hybridization Strategy using Evolutionary Algorithms. M. Schoenauer, P. Savéant, V. Vidal, Advances in Metaheuristics for Hard Optimization, 2008.
  33. Planification par satisfaction de bases de clauses. F. Maris, P. Régnier, V. Vidal, Problème SAT : défis et challenges, 2008.
  34. Recording and Minimizing Nogoods from Restarts. C. Lecoutre, L. Saïs, S. Tabary, V. Vidal, Journal on Satisfiability, Boolean Modelling and Computation 1 (3-4), 2007.
  35. Transposition Tables for Constraint Satisfaction. C. Lecoutre, L. Saïs, S. Tabary, V. Vidal, AAAI-2007, 2007.
  36. Exploiting Past and Future: Pruning by Inconsistent Partial State Dominance. C. Lecoutre, L. Saïs, S. Tabary, V. Vidal, CP-2007, 2007.
  37. Nogood Recording from Restarts. C. Lecoutre, L. Saïs, S. Tabary, V. Vidal, IJCAI-2007, 2007.
  38. Proceedings of the ICAPS-2007 Workshop Heuristics for Domain-independent Planning: Progress, Ideas, Limitations, Challenges. Blai Bonet, Carmel Domshlak, Héctor Geffner, Patrick Haslum, Malte Helmert, Jörg Hoffmann, Vincent Vidal (editors), 1st ICAPS Workshop on Heuristics for Domain-independent Planning (HDIP-2007), 2007.
  39. Tables de transposition pour la satisfaction de contraintes. C. Lecoutre, L. Saïs, S. Tabary, V. Vidal, JFPC-2007, 2007.
  40. Branching and Pruning: An Optimal Temporal POCL Planner based on Constraint Programming. V. Vidal, H. Geffner, Artificial Intelligence 170 (3), 2006.
  41. Last Conflict based Reasoning. C. Lecoutre, L. Saïs, S. Tabary, V. Vidal, ECAI-2006, 2006.
  42. Divide-and-Evolve: a New Memetic Scheme for Domain-Independent Temporal Planning. M. Schoenauer, P. Savéant, V. Vidal, EvoCOP-2006, 2006.
  43. Nogood Recording from Restarts. C. Lecoutre, L. Saïs, S. Tabary, V. Vidal, CP-2006 Workshop on the Integration of SAT and CP techniques (link), 2006.
  44. Improvement of an Optimal Temporal Planner by Giving It the Ability to Manage Resources. Z. Loukil, P. Marquis, V. Vidal, EURO-2006, 2006.
  45. The New Version of CPT, an Optimal Temporal POCL Planner based on Constraint Programming. V. Vidal, S. Tabary, IPC-2006, 2006.
  46. Recherche dirigée par le dernier conflit. C. Lecoutre, L. Saïs, S. Tabary, V. Vidal, JFPC-2006, 2006.
  47. Divide-and-Evolve : une nouvelle méta-heuristique pour la planification temporelle indépendante du domaine. M. Schoenauer, P. Savéant, V. Vidal, JFPDA-2006, 2006.
  48. Les ressources et la planification temporelle. Z. Loukil, A. Ben Hamadou, P. Marquis, V. Vidal, INFORSID-2006, 2006.
  49. Solving Simple Planning Problems with More Inference and No Search. V. Vidal, H. Geffner, CP-2005, 2005.
  50. Plus d'inférence et moins de recherche pour la résolution de problèmes de planification simples. V. Vidal, H. Geffner, JFPC-2005, 2005.
  51. Branching and Pruning: An Optimal Temporal POCL Planner based on Constraint Programming. V. Vidal, H. Geffner, AAAI-2004, 2004.
  52. A Lookahead Strategy for Heuristic Search Planning. V. Vidal, ICAPS-2004, 2004.
  53. Branching and Pruning: An Optimal Temporal POCL Planner based on Constraint Programming. V. Vidal, H. Geffner, WIPIS-2004, 2004.
  54. The YAHSP Planning System: Forward Heuristic Search with Lookahead Plans Analysis. V. Vidal, IPC-2004, 2004.
  55. CPT: An Optimal Temporal POCL Planner based on Constraint Programming. V. Vidal, H. Geffner, IPC-2004, 2004.
  56. Un planificateur temporel optimal basé sur la programmation par contraintes. V. Vidal, H. Geffner, JNPC-2004, 2004.
  57. Une stratégie d'anticipation pour la planification par recherche heuristique. V. Vidal, RFIA-2004, 2004.
  58. Planification SAT : Amélioration des codages et traduction automatique. F. Maris, P. Régnier, V. Vidal, RFIA-2004, 2004.
  59. Satplan. P. Régnier, V. Vidal, Algorithmique de la planification en IA, 2004.
  60. Graphplan. P. Régnier, V. Vidal, Algorithmique de la planification en IA, 2004.
  61. Algorithmes de planification polynomiaux pour des domaines de transport. É. Bonzon, P. Régnier, V. Vidal, Technical Report 2004-12-R, 2004.
  62. Planification BLACKBOX : Amélioration des codages. F. Maris, P. Régnier, X. Rodriguez, V. Vidal, Technical Report 2004-13-R, 2004.
  63. A Lookahead Strategy for Solving Large Planning Problems. V. Vidal, IJCAI-2003, 2003.
  64. Dossier Planification Heuristique en Intelligence Artificielle. P. Fabiani, É. Jacopin, V. Vidal, Bulletin de l'Association Française pour l'Intelligence Artificielle 56-57, 2003.
  65. A Lookahead Strategy for Heuristic Search Planning. V. Vidal, Technical Report 2002-35-R, 2002.
  66. Le moindre engagement dans une approche de la planification basée sur la procédure de Davis et Putnam. V. Vidal, JNPC-2002, 2002.
  67. Planification SAT : amélioration des codages, automatisation de la traduction et étude comparative. F. Maris, P. Régnier, V. Vidal, Technical Report 2002-39-R, 2002.
  68. Least Commitment in Graphplan. M. Cayrol, P. Régnier, V. Vidal, Artificial Intelligence 130 (1), 2001.
  69. Recherche dans les graphes de planification, satisfiabilité et stratégies de moindre engagement. Les systèmes LCGP et LCDPP. V. Vidal, PhD thesis, 2001.
  70. New Results about LCGP, a Least Committed Graphplan. M. Cayrol, P. Régnier, V. Vidal, AIPS-2000, 2000.
  71. LCGP : une amélioration de Graphplan par relâchement de contraintes entre actions simultanées. M. Cayrol, P. Régnier, V. Vidal, RFIA-2000, 2000.
  72. Contribution à la planification par compilation de plans. V. Vidal, Technical Report 00-03-R, 2000.
  73. Total Order Planning is more Efficient than we Thought. P. Régnier, V. Vidal, AAAI-1999, 1999.
  74. Comparaison expérimentale entre UCPOP et VVPLAN, un planificateur d'ordre total pour ADL. V. Vidal, P. Régnier, Technical Report 98-30-R-1, 1999.
  75. Contribution à l'amélioration de GRAPHPLAN. Formalisation, critique, modification : LCGP. V. Vidal, M. Cayrol, P. Régnier, Technical Report 99-12-R-2, 1999.
  76. Comparaison entre la planification dans les espaces d'états et dans les espaces de plans. V. Vidal, Master's thesis, 1998.

Music

ManBuss

In my spare time I play bass in a rock band, ManBuss…


Top Bottom