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Modelling Planning Problems
Vodrážka, Jindřich ; Barták, Roman (advisor) ; Chrpa, Lukáš (referee)
This thesis deals with the knowledge engineering for Automated Planning. The concept of state variables has been recently used with benefits for representation of planning problems. In this thesis the same concept is used in a novel formalism for planning domain and problem modeling. A proof-of-concept knowledge modeling tool is developed based on the new formalism. This tool is then used for modeling of example classical planning domain to show its capabilities. The export to standard domain modeling language is also implemented in the tool in order to provide connection to existing planning systems.
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Efficient Representations and Conversions of Planning Problems
Toropila, Daniel
Title E cient Representations and Conversions of Planning Problems Author Daniel Toropila Department Department of Theoretical Computer Science and Mathematical Logic Supervisor prof. RNDr. Roman Barták, Ph.D. Abstract The e ciency of all types of planning systems is strongly dependent on the in- put formulation, the structure of which must be exploited in order to provide an improved e ciency. Hence, the state-variable representation (SAS+ ) has be- come the input of choice for many modern planners. As majority of planning problems is encoded using a classical representation, several techniques for trans- lation into SAS+ have been developed in the past. These techniques, however, ignore the instance-specific information of planning problems. Therefore, we in- troduce a novel algorithm for constructing SAS+ that fully utilizes the information from the goal and the initial state. By performing an exhaustive experimental evaluation we demonstrate that for many planning problems the novel approach generates a more e cient encoding, providing thus an improved solving time. Finally, we present an overview and performance evaluation of several constraint models based on SAS+ and finite-state automata, showing that they represent a competitive alternative in the category of constraint-based planners. Keywords...
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Efficient Representations and Conversions of Planning Problems
Toropila, Daniel ; Barták, Roman (advisor) ; McCluskey, Thomas Leo (referee) ; Pěchouček, Michal (referee)
Title E cient Representations and Conversions of Planning Problems Author Daniel Toropila Department Department of Theoretical Computer Science and Mathematical Logic Supervisor prof. RNDr. Roman Barták, Ph.D. Abstract The e ciency of all types of planning systems is strongly dependent on the in- put formulation, the structure of which must be exploited in order to provide an improved e ciency. Hence, the state-variable representation (SAS+ ) has be- come the input of choice for many modern planners. As majority of planning problems is encoded using a classical representation, several techniques for trans- lation into SAS+ have been developed in the past. These techniques, however, ignore the instance-specific information of planning problems. Therefore, we in- troduce a novel algorithm for constructing SAS+ that fully utilizes the information from the goal and the initial state. By performing an exhaustive experimental evaluation we demonstrate that for many planning problems the novel approach generates a more e cient encoding, providing thus an improved solving time. Finally, we present an overview and performance evaluation of several constraint models based on SAS+ and finite-state automata, showing that they represent a competitive alternative in the category of constraint-based planners. Keywords...
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Efficient Representations and Conversions of Planning Problems
Toropila, Daniel
Title E cient Representations and Conversions of Planning Problems Author Daniel Toropila Department Department of Theoretical Computer Science and Mathematical Logic Supervisor prof. RNDr. Roman Barták, Ph.D. Abstract The e ciency of all types of planning systems is strongly dependent on the in- put formulation, the structure of which must be exploited in order to provide an improved e ciency. Hence, the state-variable representation (SAS+ ) has be- come the input of choice for many modern planners. As majority of planning problems is encoded using a classical representation, several techniques for trans- lation into SAS+ have been developed in the past. These techniques, however, ignore the instance-specific information of planning problems. Therefore, we in- troduce a novel algorithm for constructing SAS+ that fully utilizes the information from the goal and the initial state. By performing an exhaustive experimental evaluation we demonstrate that for many planning problems the novel approach generates a more e cient encoding, providing thus an improved solving time. Finally, we present an overview and performance evaluation of several constraint models based on SAS+ and finite-state automata, showing that they represent a competitive alternative in the category of constraint-based planners. Keywords...
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Modelling Planning Problems
Vodrážka, Jindřich ; Barták, Roman (advisor) ; Chrpa, Lukáš (referee)
This thesis deals with the knowledge engineering for Automated Planning. The concept of state variables has been recently used with benefits for representation of planning problems. In this thesis the same concept is used in a novel formalism for planning domain and problem modeling. A proof-of-concept knowledge modeling tool is developed based on the new formalism. This tool is then used for modeling of example classical planning domain to show its capabilities. The export to standard domain modeling language is also implemented in the tool in order to provide connection to existing planning systems.
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