Think Complexity : Complexity Science and Computational Modeling, 2/e (Paperback)

Allen Downey

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商品描述

Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you’ll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics.

Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations.

In this updated second edition, you will:

  • Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform
  • Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines
  • Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata
  • Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism

Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.

商品描述(中文翻譯)

複雜性科學使用計算方法來探索物理和社會科學。在《Think Complexity》中,您將使用圖形、細胞自動機和基於代理的模型來研究物理、生物和經濟等主題。

無論您是中級Python程序員還是計算建模的學生,您都將通過一系列的實例、練習、案例研究和易於理解的解釋來深入研究複雜系統。

在這本更新的第二版中,您將會:

- 使用NumPy數組和SciPy方法,包括基本信號處理和快速傅立葉變換
- 研究複雜物理系統的抽象模型,包括冪律、分形和粉紅噪聲,以及圖靈機
- 獲得帶有起始代碼和解決方案的Jupyter筆記本,以幫助您重新實現和擴展複雜性的原始實驗;以及計算模型,如Turmites、圖靈機和細胞自動機
- 探索科學哲學,包括科學定律的性質、理論選擇以及現實主義和工具主義

作為Python計算建模課程的教材,《Think Complexity》也幫助自學者獲得與其他主題和想法相關的寶貴經驗。