Below the list of projects cofunded by the María de Maeztu program (selected via internal calls, in this link the first one launched at the beginning of the program, and in this link the second one, launched in September 2016).
In addition, the program supports:
- the joint calls for cooperation between DTIC and the UPF Department of Experimental and Health Sciences (CEXS), also recognised as a María de Maeztu Unit of Excellence. Here the link to the second call (November 2017). The first call took place in January 2017.
- its own Open Science and Innovation program
- a pilot program to promote educational research collaborations with industry
The detail of the internal procedures for the distribution of funds associated to the program can be found here
Enhancing Usability and Dissemination of Planning Tools
Enhancing Usability and Dissemination of Planning Tools
Enhancing Usability and Dissemination of Planning Tools
Over the last few years, the Artificial Inteligence (AI) research group has developed a large number of planning tools. Although these have been used and described in conference and journal papers, there is still a long way to go in order to enhance their usability and adoption for the large number of potential users of the tools.
This project aims at enhancing the outreach of the planning tools developed within the AI group. For that, two main lines will be pursued:
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Bringing into good shape, by following standard software engineering best practices, a number of research prototypes developed within the group which have been successfully used in several publications, but are still somewhat unpolished and not ready for production mode. Examples of these tools would be the novel functional planner FS, a parser for a number of common planning modeling languages, a state-of-the-art multi-agent planner, or a state-of-the-art temporal planner, etc.
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Integrating some of these standard planning tools with ROS, the Robot Operating System, which will foster their use within the large number of users of ROS in the robotics community that as of now have almost no ready-to-use options when it comes to performing the type of task planning where that the AI group tools excel.
To know more:
- Presentation of the project at the Data-driven Knowledge Extraction Workshop, June 2016 (slides)
- Work-in-progress group’s main Github repository at aig-upf.github.io.
- The importance of existential quantification in automatic planning (UPF news, 07/07/2016)
- AI provides solutions to planning problems (UPF news, 22/07/2016)
Principal researchers
Héctor Geffner Anders JonssonResearchers
Guillem Francès Jonathan Ferrer-MestresRelated Assets:
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Algorithms for solving temporal planning problems
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Automated programming framework
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Segovia-Aguas, J, Jiménez, S, Jonsson, A. Unsupervised Classification of Planning Instances. Proceedings of the 27th International Conference on Automated Planning and Scheduling (ICAPS'17)
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Segovia Aguas J, Jiménez S, Jonsson A. Generating context-free grammars using classical planning. IJCAI International Joint Conference on Artificial Intelligence; 2017 Aug 19-25; Melbourne, Australia.
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Francès, G., Ramírez, M., Lipovetzky, N. and Geffner, H.Purely Declarative Action Representations are Overrated: Classical Planning with Simulators. In Proc. of the 26th Int. Joint Conf. on Artificial Intelligence (IJCAI 2017)
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IJCAI Distinguished Paper Award for work in hierarchical finite state controllers
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Enhancing usability and dissemination of software, the experience by Daniel Furelos
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Bucchiarone A, Khandokar F, Furelos D, Jonsson A, Mourshed M. Collective Adaptation through Concurrent Planning: the Case of Sustainable Urban Mobility. 7th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018)
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Furelos-Blanco D, Bucchiarone A, Jonsson A. CARPooL: Collective Adaptation using concuRrent PLanning. 7th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018)
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[MSc thesis] Cross-Entropy method for Kullback-Leibler control in multi-agent systems
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[MSc thesis] Resolution of concurrent planning problems using classical planning
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Smart Carpooling demo using a temporal planner
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[PhD thesis] Effective planning with expressive languages
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The multiagent extension for the PDDL parser
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Lotinac D, Jonsson A. Constructing Hierarchical Task Models Using Invariance Analysis. Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI'16), 2016
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Segovia-Aguas J, Jiménez S, Jonsson A. Hierarchical Finite State Controllers for Generalized Planning. International Joint Conference on Artificial Intelligence. 2016.
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Lotinac D, Segovia-Aguas J, Jiménez S, Jonsson A. Automatic Generation of High-Level State Features for Generalized Planning. International Joint Conference on Artificial Intelligence. 2016
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Francès G, Geffner H. E-STRIPS: Existential Quantification in Planning and Constraint Satisfaction. Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016)
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2018 Artificial Intelligence Dissertation Award from the European Artificial Intelligence Association awarded to Javier Segovia
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Furelos-Blanco D, Jonsson A, Palacios H, Jiménez S. Forward-Search Temporal Planning with Simultaneous Events. ICASP’18 Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS 2018)
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Furelos-Blanco D, Jonsson A. Solving Concurrent Multiagent Planning using Classical Planning. 6th Workshop on Distributed and Multi-Agent Planning (DMAP 2018)