Statistical Reinforcement Learning: Modern Machine Learning Approaches (Hardcover)
暫譯: 統計強化學習：現代機器學習方法 (精裝版)

Masashi Sugiyama

Statistical Reinforcement Learning: Modern Machine Learning Approaches (Hardcover)

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商品描述

Reinforcement learning (RL) is a framework for decision making in unknown environments based on a large amount of data. Several practical RL applications for business intelligence, plant control, and game players have been successfully explored in recent years. Providing an accessible introduction to the field, this book covers model-based and model-free approaches, policy iteration, and policy search methods. It presents illustrative examples and state-of-the-art results, including dimensionality reduction in RL and risk-sensitive RLm. The book provides a bridge between RL and data mining and machine learning research.

商品描述(中文翻譯)

強化學習（Reinforcement Learning, RL）是一種基於大量數據在未知環境中進行決策的框架。近年來，已成功探索幾個實際的 RL 應用於商業智慧、工廠控制和遊戲玩家。本書提供了該領域的易懂介紹，涵蓋了基於模型和無模型的方法、策略迭代以及策略搜尋方法。書中呈現了插圖範例和最先進的結果，包括 RL 中的降維和風險敏感的 RL。本書為 RL 與資料探勘和機器學習研究之間架起了一座橋樑。

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