Preface (First Driving Force)
- Critical thinking is one of the fundamental spirits of science.
- Why has science become the “first driving force” for human progress? Because a defining feature of science is its constant progression, i.e., the continuous refinement through critical thinking.
- Science belongs to itself and its own reasoning—why? Why isn’t it subordinate to theology or philosophy? Because it is universal and independent. – There are uncertainties.
Introduction
- What is reductionism, and what problems does it entail?
- What led to the emergence of complexity science?
- Four perspectives on complex systems: information, computation, dynamics, chaos, and evolution.
Chapter 1: What Is Complexity?
- A brief introduction to complexity from various angles (with examples across different fields).
Chapter 7: Measuring Complexity
- Occam’s razor principle: “Entities should not be multiplied unnecessarily.” Prefer simpler explanations unless more complex assumptions provide compelling evidence. The key point is, “If a complex assumption is chosen, it must provide sufficient justification for its validity.”
- Experience is needed to determine what constitutes “simplicity.”
Chapter 10: Cellular Automata
- Complex systems in nature are decentralized. Each individual unit (e.g., cells, humans) operates independently.
Chapter 13: How to Make Analogies
- In Chapter 12, we observed how ant colonies search for food: the shortest path to the best food source becomes increasingly marked by strong pheromones, attracting more ants. However, at all times, some ants still follow weaker scent trails or randomly explore, which could lead to discovering new food sources. [Examples include ant colonies, immune systems, etc.]
Summary
- Continuous reflection is a universal logic for progress. This essay approaches complexity science from its core principles: what complex systems are and how they can be studied. Complex systems arise from a large number of independent individuals and exhibit emerging behaviors (properties), self-organization, and adaptability.
- Are there universal laws? Not yet discovered.
- Key models: cellular automata, genetic algorithms, neural networks, agent-based models.