<sc>ghost</sc>: A Combinatorial Optimization Framework for Real-Time Problems
نویسندگان
چکیده
منابع مشابه
ghost: A Combinatorial Optimization Framework for Real-Time Problems
This paper presents GHOST, a combinatorial optimization framework that a Real-Time Strategy (RTS) AI developer can use to model and solve any problem encoded as a constraint satisfaction/optimization problem. We show a way to model three different problems as a constraint satisfaction/optimization problem, using instances from the RTS game StarCraft as test beds. Each problem belongs to a speci...
متن کاملA Tabu Search Framework for Dynamic Combinatorial Optimization Problems
Combinatorial Optimization problems are often computationally expensive. Due to the NP-complete nature of such problems, finding an optimal solution is impractical. Many generic techniques have been developed to approximate such problems and find reasonably good or partial solutions. A few solutions examined apply these techniques to dynamic optimization problems where the domain is subject to ...
متن کاملA Hierarchical Decomposition Framework for Modeling Combinatorial Optimization Problems
Complex Optimization Problems has existed in many fields of science, including economics, healthcare, logistics and finance where a complex problem has to be solved. Thus, modeling a complex problem is a fundamental step to relax its complexity and achieve to a final solution of the master problem. Hierarchical optimization is a main step in optimization problems handling process. It consists o...
متن کاملCombinatorial Online Optimization in Real Time
Optimization is the task of finding an optimum solution to a given problem. When the decision variables are discrete we speak of a combinatorial optimization problem. Such a problem is online when decisions have to be made before all data of the problem are known. And we speak of a real-time online problem when online decisions have to be computed within very tight time bounds. This paper surve...
متن کاملA Framework for Adapting Population-Based and Heuristic Algorithms for Dynamic Optimization Problems
In this paper, a general framework was presented to boost heuristic optimization algorithms based on swarm intelligence from static to dynamic environments. Regarding the problems of dynamic optimization as opposed to static environments, evaluation function or constraints change in the time and hence place of optimization. The subject matter of the framework is based on the variability of the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Computational Intelligence and AI in Games
سال: 2016
ISSN: 1943-068X,1943-0698
DOI: 10.1109/tciaig.2016.2573199