Heuristic Search Exploiting Non-additive and Unit Properties for RTS-game Unit Micromanagement
نویسندگان
چکیده
This paper presents an approach that integrates fuzzy integral and fast heuristic search for improving the quality of unit micromanagement in the popular RTS game StarCraft. Unit micromanagement, i.e., detailed control of units in combat, is one of the most challenging problems posed by RTS games and is often tackled with search algorithms such as Minimax or Alpha-Beta. Due to vast state and action spaces, the game tree is often very large, and search algorithms must rely on evaluation methods from a certain limited depth rather than exploring deeper into the tree. We therefore attempt to apply fuzzy integral and aim for an evaluation method with high accuracy in the search. To achieve this aim, we propose a new function that allows fuzzy integral to cope with not only non-additive properties but also unit properties in RTS games. Experimental results are reported at the end of this paper, showing that our approach outperforms an existing approach in terns of win rates in this domain.
منابع مشابه
An Analysis of Model-Based Heuristic Search Techniques for StarCraft Combat Scenarios
Real-Time Strategy games have become a popular test-bed for modern AI system due to their real-time computational constraints, complex multi-unit control problems, and imperfect information. One of the most important aspects of any RTS AI system is the efficient control of units in complex combat scenarios, also known as micromanagement. Recently, a model-based heuristic search technique called...
متن کاملDynamic 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 combin...
متن کاملIncorporating Search Algorithms into RTS Game Agents
Real-time strategy (RTS) games are known to be one of the most complex game genres for humans to play, as well as one of the most difficult games for computer AI agents to play well. To tackle the task of applying AI to RTS games, recent techniques have focused on a divide-and-conquer approach, splitting the game into strategic components, and developing separate systems to solve each. This tre...
متن کاملNeuroevolution for Micromanagement in the Real-Time Strategy Game Starcraft: Brood War
Real-Time Strategy (RTS) games have become an attractive domain for AI research in recent years, due to their dynamic, multi-agent and multi-objective environments. Micromanagement, a core component of many RTS games, involves the control of multiple agents to accomplish goals that require fast, real time assessment and reaction. In this paper, we present the application and evaluation of a Neu...
متن کاملBayesian Networks for Micromanagement Decision Imitation in the RTS Game Starcraft
Real time strategy (RTS) games provide various research areas for Artificial Intelligence. One of these areas involves the management of either individual or small group of units, called micromanagement. This research provides an approach that implements an imitation of the player’s decisions as a mean for micromanagement combat in the RTS game Starcraft. A bayesian network is generated to fit ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- JIP
دوره 23 شماره
صفحات -
تاریخ انتشار 2015