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AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
May 27, 2026 · Artificial Intelligence

Balancing Information Value and Platform Survival in Underwater UUV C2 Decision Making

The article presents a comprehensive C2 decision framework for underwater UUVs, defining core variables, rule‑based and game‑theoretic models, POMDP and Monte‑Carlo solutions, risk‑aware algorithms, multi‑UUV consensus, and practical three‑layer rule implementations to balance information gain against platform survivability.

Autonomous SystemsC2Decision Theory
0 likes · 14 min read
Balancing Information Value and Platform Survival in Underwater UUV C2 Decision Making
Model Perspective
Model Perspective
Apr 12, 2026 · Industry Insights

Why Loud Quit Threats Stay and Silent Workers Actually Leave

Applying decision‑theory and game‑theoretic models, the article explains why employees who loudly threaten to quit often stay, while silent workers quietly prepare to leave, describing utility comparisons, a complaint‑as‑pressure‑release mechanism, cheap‑talk signaling, and two stable workplace equilibria with practical implications for observers, managers, and individuals.

Decision TheoryPsychologyemployee turnover
0 likes · 8 min read
Why Loud Quit Threats Stay and Silent Workers Actually Leave
Model Perspective
Model Perspective
Mar 31, 2026 · Industry Insights

Why Campus Dating Apps Thrive: The Real Power Behind Algorithmic Matching

The SJTU Date platform demonstrates that algorithmic matching succeeds not because of superior prediction but by fulfilling a genuine demand, reducing social initiation costs, and offering users autonomy through a transparent, content‑based filtering system, while highlighting the limits of such algorithms in predicting long‑term compatibility.

Decision Theoryalgorithmic matchingassignment problem
0 likes · 9 min read
Why Campus Dating Apps Thrive: The Real Power Behind Algorithmic Matching
Model Perspective
Model Perspective
Oct 13, 2025 · Fundamentals

Timing the Harvest: The Optimal Stopping Theory Behind a Classic Chinese Poem

Using the Tang poem 'When the flower blooms, seize it' as a metaphor, this article formulates the optimal stopping problem with Gaussian value curves, survival probabilities, discounting, risk attitudes, Bayesian learning, and exploration‑exploitation trade‑offs, revealing when to act before the perfect moment fades.

Decision TheoryOptimal Stoppingbayesian learning
0 likes · 12 min read
Timing the Harvest: The Optimal Stopping Theory Behind a Classic Chinese Poem
Model Perspective
Model Perspective
Apr 22, 2025 · Artificial Intelligence

What Are Herbert Simon’s Four Decision-Making Models and Why They Matter

The article reviews Herbert Simon’s four influential decision‑making models—Subjective Expected Utility, Behavioral, Intuitive, and Darwinian—explaining their key features, applications, and limitations, and shows how they illuminate rational and adaptive choices in economics, psychology, and organizational behavior.

Artificial IntelligenceBounded RationalityDarwinian Model
0 likes · 9 min read
What Are Herbert Simon’s Four Decision-Making Models and Why They Matter
Model Perspective
Model Perspective
Mar 21, 2024 · Fundamentals

How the “Maximum Regret Principle” Guides Decision‑Making: A Mathematical Model Explained

The article introduces Zhang Ruimin’s “maximum regret principle,” explains its mathematical formulation using regret matrices and utility functions, and demonstrates its application through a concrete investment decision example that shows how minimizing the worst‑case regret leads to robust choices.

Decision Theorybusiness strategymathematical modeling
0 likes · 5 min read
How the “Maximum Regret Principle” Guides Decision‑Making: A Mathematical Model Explained
Model Perspective
Model Perspective
Jan 6, 2023 · Fundamentals

When to Stop Searching? Unveiling the 37% Rule with Simulations

This article explores the classic optimal‑stopping (secretary) problem through a philosophical story, mathematical analysis, Python simulations, and a proof that the best strategy is to reject roughly the first 37 % of candidates, yielding about a 40 % chance of selecting the optimal option.

37% ruleDecision TheoryOptimal Stopping
0 likes · 11 min read
When to Stop Searching? Unveiling the 37% Rule with Simulations
Model Perspective
Model Perspective
Jul 11, 2022 · Operations

Deterministic vs. Stochastic Decisions: Mastering Time Value of Money Calculations

The article explains the distinction between deterministic and stochastic decision-making, outlines common operations‑research methods such as linear and nonlinear programming, and details cash‑flow concepts and the mathematical formulas for compound interest, present and future values, annuities, and capital recovery and storage factors.

Decision TheoryOperations Researchcash flow
0 likes · 6 min read
Deterministic vs. Stochastic Decisions: Mastering Time Value of Money Calculations