Planning in hybrid systems has been gaining research interest in the Artificial Intelligence community in recent years. Hybrid systems allow for a more accurate representation of real world problems, though solving them is very challenging due to complex system dynamics and a large model feature set. We developed DiNo, a new planner designed to tackle problems set in hybrid domains. DiNo is based on the discretise and validate approach and uses the novel Staged Relaxed Planning Graph+ (SRPG+) heuristic

Piotrowski, W., Fox, M., Long, D., Magazzeni, D., Mercorio, F. (2016). Heuristic Planning for PDDL+ Domains. In Proceedings of Planning for Hybrid Systems, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 13, 2016 (pp.4254-4255).

Heuristic Planning for PDDL+ Domains

MERCORIO, FABIO
2016

Abstract

Planning in hybrid systems has been gaining research interest in the Artificial Intelligence community in recent years. Hybrid systems allow for a more accurate representation of real world problems, though solving them is very challenging due to complex system dynamics and a large model feature set. We developed DiNo, a new planner designed to tackle problems set in hybrid domains. DiNo is based on the discretise and validate approach and uses the novel Staged Relaxed Planning Graph+ (SRPG+) heuristic
Si
paper
PDDL+, Planning, Model Checking, Hybrid Systems
English
The AAAI Workshop on Planning for Hybrid Systems February 12–17
978-1-57735-759-9
http://www.aaai.org/Library/Workshops/ws16-12.php
Piotrowski, W., Fox, M., Long, D., Magazzeni, D., Mercorio, F. (2016). Heuristic Planning for PDDL+ Domains. In Proceedings of Planning for Hybrid Systems, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 13, 2016 (pp.4254-4255).
Piotrowski, W; Fox, M; Long, D; Magazzeni, D; Mercorio, F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/140811
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