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Reinforcement learning began to perform at human-level success in game intelligence after deep learning revolution. Geometry Friends is a puzzle game, where we can benefit from deep learning and expect to have successful game playing agents. In the game, agents are collecting targets in two dimensional environment and they try to overcome obstacles...
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Citations
... Ozgen et al. [26] proposed a circle agent that also resorts to reinforcement learning. Similar to the Supervised DL Agent, the learning is done by having stacked frames as input via a convolutional neural network, where the resulting image is processed into states. ...
Game AI competitions are important to foster research and development on Game AI and AI in general. These competitions supply different challenging problems that can be translated into other contexts, virtual or real. They provide frameworks and tools to facilitate the research on their core topics and provide means for comparing and sharing results. A competition is also a way to motivate new researchers to study these challenges. In this document, we present the Geometry Friends Game AI Competition. Geometry Friends is a two-player cooperative physics-based puzzle platformer computer game. The concept of the game is simple, though its solving has proven to be difficult. While the main and apparent focus of the game is cooperation, it also relies on other AI-related problems such as planning, plan execution, and motion control, all connected to situational awareness. All of these must be solved in real-time. In this paper, we discuss the competition and the challenges it brings, and present an overview of the current solutions.
Game artificial intelligence (AI) competitions are important to foster research and development on Game AI and AI in general. These competitions supply different challenging problems that can be translated into other contexts, virtual or real. They provide frameworks and tools to facilitate the research on their core topics and provide means for comparing and sharing results. A competition is also a way to motivate new researchers to study these challenges. In this article, we present the
Geometry Friends
game AI competition.
Geometry Friends
is a two-player cooperative physics-based puzzle platformer computer game. The concept of the game is simple, though its solving has proven to be difficult. While the main and apparent focus of the game is cooperation, it also relies on other AI-related problems such as planning, plan execution, and motion control, all connected to situational awareness. All of these must be solved in real-time. In this article, we discuss the competition and the challenges it brings, and present an overview of the current solutions.
In applying reinforcement learning to a different environment, relearning is generally required. The relearning, however, is time-consuming, and therefore a method without the relearning should be developed. This paper proposes a reinforcement learning method with generalization ability for solving an optimal routing problem with a given set of multiple goal positions. The proposed method can rapidly find the optimal route for any set of the multiple goal positions once a reinforcement learning agent learns. In the proposed method, a graph search algorithm determines the visiting order of the goal positions, and an ordinary learning algorithm such as Q-learning determines each route between goal positions. The performance of the proposed method is evaluated through numerical experiments.
