Dynamic real-time hierarchical heuristic search for pathfinding.

Movement of Units in Real-Time Strategy (RTS) Games is a non-trivial and challenging task mainly due to three factors which are constraints on CPU and memory usage, dynamicity of the game world, and concurrency. In this paper, we are focusing on finding a novel solution for solving the pathfinding problem in RTS Games for the units which are controlled by the computer. The novel solution combines two AI Planning approaches: Hierarchical Task Network (HTN) and Real-Time Heuristic Search (RHS). In the proposed solution, HTNs are used as a dynamic abstraction of the game map while RHS works as planning engine with interleaving of plan making and action executions. The article provides algorithmic details of the model while the empirical details of the model are obtained by using a real-time strategy game engine called ORTS (Open Real-time Strategy). The implementation of the model and its evaluation methods are in progress however the results of the automatic HTN creation are obtained for a small scale game map

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications