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Memorizing and retrieval of a face of board is problem on constructing a board game agent because board games have problem of state explosion, “The curse of dimensionality.” We propose to memorize by Self-Organizing Maps and to retrieve from it. The problem of memorizing by SOM is determination of the thresholds which retrieve properly a state(More)
Recently, the researches that create agents which play board games have been studied actively. According to those studies, those agents have abilities that are comparable to the strongest experts. However, it can be said that those agents depend on the computational capability because that abilities of those agents are realized by thousands of lookahead(More)
Recently, drones have been used for many purposes. The investigation of tree growth in a forest is also one of the expectations for drone applications. The aim of this paper is that a drone recognizes a color marker which is set to a tree from an image, and a drone approaches to that tree, and then return to the goal zone. To solve the task, we propose to(More)
—Reinforcement learning is suitable for navigation of a mobile robot due to its learning ability without supervised information. Reinforcement learning, however, has difficulties. One is its slow learning, and the other is the necessity of specifying its parameter values without prior information. We proposed to introduce sensory signals into reinforcement(More)
Recently, the researches that regard puzzle games as nonlinear optimization problems have been studied. The puzzles, which are N-Queen problem and Knapsack problem, are called NP-hard or NP-complete problem, hence the studies have been actively. On the other hand, there are a lot of puzzle game in the world, nevertheless many puzzle game have not been(More)
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