We describe HTN-MAKER, an algorithm for learning hierarchical planning knowledge in the form of decomposition methods for Hierarchical Task Networks (HTNs). HTNMAKER takes as inpu...
Strategy planning is crucial to control a group to achieve a number of tasks in a closed area full of obstacles. In this study, genetic programming has been used to evolve rule-ba...
— In order to define an architecture for task and motion planning of a mobile robot, we propose the CellRRT path planner that combines the advantages of planning approaches by d...
We combine mixed integer linear programming (MILP) and constraint programming (CP) to solve planning and scheduling problems. Tasks are allocated to facilities using MILP and sche...
In this paper, we analyze the impact of different automatic annotation methods on the performance of supervised approaches to the complex question answering problem (defined in th...