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A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft
This paper presents an overview of the existing work on AI for real-time strategy (RTS) games. Specifically, we focus on the work around the game StarCraft, which has emerged in the past few years asExpand
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The Combinatorial Multi-Armed Bandit Problem and Its Application to Real-Time Strategy Games
Game tree search in games with large branching factors is a notoriously hard problem. In this paper, we address this problem with a new sampling strategy for Monte Carlo Tree Search (MCTS)Expand
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Case-Based Planning and Execution for Real-Time Strategy Games
Artificial Intelligence techniques have been successfully applied to several computer games. However in some kinds of computer games, like real-time strategy (RTS) games, traditional artificialExpand
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Ensemble Case-Based Reasoning: Collaboration Policies for Multiagent Cooperative CBR
Multiagent systems offer a new paradigm to organize AI applications. Our goal is to develop techniques to integrate CBR into applications that are developed as multiagent systems. CBR offers theExpand
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Combinatorial Multi-armed Bandits for Real-Time Strategy Games
  • S. Ontañón
  • Mathematics, Computer Science
  • J. Artif. Intell. Res.
  • 29 March 2017
Games with large branching factors pose a significant challenge for game tree search algorithms. In this paper, we address this problem with a sampling strategy for Monte Carlo Tree Search (MCTS)Expand
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ON‐LINE CASE‐BASED PLANNING
Some domains, such as real‐time strategy (RTS) games, pose several challenges to traditional planning and machine learning techniques. In this article, we present a novel on‐line case‐based planningExpand
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Adversarial Hierarchical-Task Network Planning for Complex Real-Time Games
Real-time strategy (RTS) games are hard from an AI point of view because they have enormous state spaces, combinatorial branching factors, allow simultaneous and durative actions, and players haveExpand
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Game-Tree Search over High-Level Game States in RTS Games
From an AI point of view, Real-Time Strategy (RTS) games are hard because they have enormous state spaces, they are real-time and partially observable. In this paper, we present an approach to deployExpand
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The VGLC: The Video Game Level Corpus
Levels are a key component of many different video games, and a large body of work has been produced on how to procedurally generate game levels. Recently, Machine Learning techniques have beenExpand
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Collaborative Case Retention Strategies for CBR Agents
Empirical experiments have shown that storing every case does not automatically improve the accuracy of a CBR system. Therefore, several retain policies have been proposed in order to select whichExpand
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