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Comparison of Classical Planning Methods
Černianska, Rebeka ; Zbořil, František (referee) ; Zbořil, František (advisor)
This bachelor's thesis deals with the topic of automated planning and the methods which deal with its problems. The analysis and comparison of the methods STRIPS, Graphplan and HTN takes place, which implement different approaches to planning. Their performance is tested on typical planning problems, which focus on various planning challenges. The goal was to find suitable planning problems for each of the methods, as well as their strong and weak points regarding the given problem. For testing purposes, existing implementations of the methods were used, which showcase their behaviour.
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Comparison of Classical Planning Methods
Černianska, Rebeka ; Zbořil, František (referee) ; Zbořil, František (advisor)
This bachelor's thesis deals with the topic of automated planning and the methods which deal with its problems. The analysis and comparison of the methods STRIPS, Graphplan and HTN takes place, which implement different approaches to planning. Their performance is tested on typical planning problems, which focus on various planning challenges. The goal was to find suitable planning problems for each of the methods, as well as their strong and weak points regarding the given problem. For testing purposes, existing implementations of the methods were used, which showcase their behaviour.
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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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Comparing reactive techniques to classical planning for intelligent virtual agents
Černý, Martin ; Gemrot, Jakub (advisor) ; Balyo, Tomáš (referee)
Many contemporary computer games can be described as dynamic real-time simulations inhabited by autonomous intelligent virtual agents (IVAs) where most of the environment structure is immutable and navigating through the environment is one of the most common activities. Though controlling the behaviour of such agents seems perfectly suited for action planning techniques, planning is not widely adopted in existing games. This paper attempts to answer the question whether the current academic planning technology is ready for integration to existing games and under which conditions. The paper compares reactive techniques to classical planning in handling the action selection problem for IVAs in game-like environments. Several existing classical planners that occupied top positions in the International Planning Competition were connected to the virtual environment of Unreal Development Kit via the Pogamut platform. Performance of IVAs employing those planners and IVAs with reactive architecture was measured on a class of game like test environments under different levels of external interference. It was shown that agents employing classical planning outperform reactive agents only if the size of the planning problem is small or if the environment changes are either hostile to the agent or not very frequent.
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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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Comparing reactive techniques to classical planning for intelligent virtual agents
Černý, Martin ; Gemrot, Jakub (advisor) ; Balyo, Tomáš (referee)
Many contemporary computer games can be described as dynamic real-time simulations inhabited by autonomous intelligent virtual agents (IVAs) where most of the environment structure is immutable and navigating through the environment is one of the most common activities. Though controlling the behaviour of such agents seems perfectly suited for action planning techniques, planning is not widely adopted in existing games. This paper attempts to answer the question whether the current academic planning technology is ready for integration to existing games and under which conditions. The paper compares reactive techniques to classical planning in handling the action selection problem for IVAs in game-like environments. Several existing classical planners that occupied top positions in the International Planning Competition were connected to the virtual environment of Unreal Development Kit via the Pogamut platform. Performance of IVAs employing those planners and IVAs with reactive architecture was measured on a class of game like test environments under different levels of external interference. It was shown that agents employing classical planning outperform reactive agents only if the size of the planning problem is small or if the environment changes are either hostile to the agent or not very frequent.
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Petrobras Planning Domain: PDDL Modeling and Solving
Hanes, Martin ; Toropila, Daniel (advisor) ; Gemrot, Jakub (referee)
The thesis explores Petrobras domain from the challenge track of the ICKEPS 2012 competition, which is an example of a difficult problem stand- ing on the borderline between planning and scheduling. It describes state-of-art techniques of the modern artificial intelligence that were chosen for this purpose. It guides the reader in the process of modeling the Petrobras domain in PDDL language and explains the results provided by the existing tools used within plan- ning community. In the end it compares the results of the chosen approach to the other approaches used in ICKEPS 2012 competition, showing that the existing sequential planning systems are usable only for solving smaller problem instances of this domain.
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