Chapter 6 · begins on page 225
Leadership and Rules: Inspection
The models
Each model in the book is stated on one card: who decides, when, with what information and commitment, what they get, what they may do, and the question it answers.
Dresher's game · p. 252
What can the inspector guarantee, and how does it move when one assumption changes?
Model N · p. 255
What should the inspector announce, and how much of the gain is commitment and how much information?
Model N, the worked case's reading · p. 262
What does deterrence cost compliant inspectees, what does a margin cost, and which error rate is worth more per unit?
What is proved, in words
The book follows each result with one sentence that says what it means without symbols. The formal statement is a click away; the proofs are in the book.
Proposition 6.2 · Recursion and the base case · p. 253
Dresher's inspection game is solved by a recursion of two-by-two games: with one inspection over two events the inspector's value is , and over events .
Proposition 6.3 · Full normal form · p. 254
Writing out every plan of both sides confirms the recursion's value and exhibits the inspectee's optimal plan in full.
Proposition 6.4 · Revealed inspection · p. 254
If the inspectee sees each inspection decision before choosing and there are fewer inspections than events, inspection cannot prevent the violation: it goes through in some uninspected event, and the value is .
Proposition 6.8 · Nash equilibrium · p. 257
Without commitment the non-zero-sum inspection game has a single mixed equilibrium: at the base parameters the inspector inspects a third of the time and the inspectee violates two thirds of the time.
Proposition 6.9 · Inspector leadership, · p. 257
An inspector that announces its inspection probability can deter violation at the threshold rate and halves its loss, from to — if ties are read in its favour; otherwise that value is only approached.
Proposition 6.11 · Value of the optimal rule · p. 258
At the base parameters, an inspector that commits to a rule responding to an informative noisy signal does better still (with ties in its favour; otherwise the value is approached): it inspects after a flag more readily than after a clear signal, and the formula prices deterrence in terms of the signal's error rates.
The worked case
From page 242 · sources checked 9 November 2026
Verifying where controlled chips are
What does a verification rule cost compliant licensees, what does a margin of deterrence cost, and which improvement in the check is worth more?
The mapping, the network and what the mathematics licenses →A parallax in history
1930 · Chapter 6 · p. 248
A line on the hull, a document on board
London, 1930: a load line certificate accepted abroad; port control checks paper against hull
Port state control, 2025: shared inspection records and risk-based selection (Exercise 6.4 (p. 251))
The people
Chapter 6 · Leadership and Rules: Inspection
Melvin Dresher
1911 – 1992
Mathematician, educated at Lehigh University (bachelor's degree, 1933) and Yale (doctorate, 1937); by the late 1940s he was working on game theory at the RAND Corporation. In January 1950 he and Merrill Flood planned and ran the experiment with the game later known as the prisoner's dilemma. His book presents two-person games together with their computational methods, and his 1962 memorandum analyses the recursive inspection game with which this chapter begins.
Main works
- Games of Strategy: Theory and Applications (1961)
- A Sampling Inspection Problem in Arms Control Agreements: A Game-Theoretic Analysis (RAND RM-2972-ARPA, 1962)
Chapter 6 · Leadership and Rules: Inspection
Michael Maschler
1927 – 2008
Mathematician at the Hebrew University of Jerusalem. In cooperative game theory he introduced, with Robert Aumann, the bargaining set and, with Morton Davis, the kernel. With Aumann, in collaboration with Richard Stearns, he developed repeated games with incomplete information in a research project reported to the US Arms Control and Disarmament Agency in 1965–1968. His papers on the inspector's non-constant-sum game studied inspector leadership — an inspection policy announced in advance — including how the result depends on the way the inspectee resolves indifference.
Main works
- “The bargaining set for cooperative games”, with R. J. Aumann (1964)
- “The kernel of a cooperative game”, with M. Davis (NRLQ 12, 1965)
- “A price leadership method for solving the inspector's non-constant-sum game” (NRLQ 13, 1966)
- Repeated Games with Incomplete Information, with R. J. Aumann, in collaboration with R. E. Stearns (1995)
- Game Theory, with E. Solan and S. Zamir (2013)
Chapter 6 · Leadership and Rules: Inspection
Yuri B. Germeier
1918 – 1975
Mathematician at the Computing Centre of the USSR Academy of Sciences and at Moscow State University, where in 1970 he founded and first headed the Department of Operations Research of the Faculty of Computational Mathematics and Cybernetics. He used guaranteed-result criteria in operations research and in games with non-opposed interests, and studied what a leader can secure by announcing a choice or a response rule when the follower's interests are not fully known. With N. N. Moiseev he also studied hierarchical control systems.
Main works
- Introduction to the Theory of Operations Research (in Russian, Nauka, 1971)
- “On two-person games with a fixed sequence of moves” (in Russian, DAN SSSR 198(5), 1971)
- Games with Non-Opposed Interests (in Russian, Nauka, 1976; English: Non-Antagonistic Games, 1986)