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A game whose players' utilities are specified separately, without assuming a fixed sum. Improving one player's utility need not worsen another's. A finite perfect-information game can be solved by backward induction using entire utility tuples and each moving player's own coordinate, as in max-n search.

Backward induction with an $n$-component utility vector. At a node controlled by player $i$, evaluate each child, choose a child maximizing coordinate $i$ and copy its entire vector. A fixed tie rule makes the returned vector well defined. By mathematical induction from terminal positions, the selected continuation is a best response at every node of a finite perfect-information game, giving a pure strategy subgame perfect equilibrium. The vector must be copied intact; separate coordinatewise maxima need not describe any attainable outcome.

Propagate an entire utility pair from a child chosen to maximize the component of the player whose turn it is. This is the two-player case of max-n search. At a terminal node let $V(s)=(U_A(s),U_B(s))$. At an A-node chooseand at a B-node replace $V_A$ by $V_B$. Do not maximize the two coordinates independently: their separate maxima may belong to incompatible outcomes. Fix a tie rule, such as the first child in the specified order. The rule recursively gives a pure strategy subgame perfect equilibrium in a finite perfect-information game: backward induction makes the moving player's selected continuation a best response at every node.^[ref]

In the original Figure 2, each of the three children of the root belongs to B. The left B-node prefers its first leaf because $1>0$, the middle B-node prefers its first leaf because $2>-2$, and the right B-node prefers its second leaf because $3>1$. Their propagated utility pairs, from left to right, areAt the root A compares $1,-1,-1$ and chooses the left child. Thus the root pair is $(1,1)$, with play following the root's left branch and then that B-node's first branch. No tie affects this outcome.

The equilibrium assignment is $(S_1,S_2,S_3,S_4)\mapsto (r_2,r_3,r_4,r_1)$, with utility vector $(0.7,0.7,0.9,0.4)$. Apply backward induction to the finite perfect-information game, accounting for the two friendship pairs in every terminal assignment. Student $S_4$ receives the last room and has no remaining choice. Given the first two rooms, $S_3$ chooses the remaining room maximizing their own room value plus $0.4$ if adjacent to $S_2$.

The following complete third-stage comparisons summarize the continuations. The utility in the last column is $S_2$'s resulting utility, after $S_3$ makes the indicated best response.

For example, after $S_1$ takes $r_2$ and $S_2$ takes $r_3$, student $S_3$ compares $r_1$, giving $0$, with $r_4$, giving $0.5+0.4=0.9$. Choosing $r_4$ also gives $S_2$ the adjacency bonus, making $U_2=0.3+0.4=0.7$. The last room $r_1$ is adjacent to $S_1$'s $r_2$.

The table makes $S_2$ choose $r_3,r_3,r_2,r_2$ after first-stage choices $r_1,r_2,r_3,r_4$, respectively. Their resulting consequences for $S_1$ are $0.5,0.7,0$, and either $0$ or $0.4$. Thus $S_1$ strictly prefers $r_2$, proving the displayed outcome.

There is an off-path tie for $S_3$ after $(r_4,r_2)$, so the entire subgame perfect equilibrium strategy profile need not be unique. Either choice, or any mixture of them, gives $S_1$ at most $0.4$ after choosing $r_4$, below $0.7$. The equilibrium assignment on the played path is therefore unaffected by this tie. Specifying these optimal continuations at every history, including the unplayed ones, supplies a subgame perfect equilibrium rather than merely a proposed path.

Measure all payoffs in millions of dollars, in the order (Ann, Bob). Since both players maximize expected money, those numbers are already their expected utility scale.

In the extensive-form game, Ann moves first. Staying out terminates at $(2,6)$. Entering leads to Bob's observed decision between fighting, with terminal payoffs $(1,1)$, and acquiescing, with terminal payoffs $(3,3)$. Each decision node is its own information set, so this is a perfect-information game.

The corresponding normal-form game gives Ann the pure strategies $O$ (stay out) and $E$ (enter), and Bob the complete contingent pure strategies $F$ (fight if entry occurs) and $A$ (acquiesce if entry occurs). The payoff matrix isThe pure strategy Nash equilibria are $(O,F)$ and $(E,A)$. Against $F$, Ann prefers $O$; against $A$, Ann prefers $E$. When Ann stays out, Bob's contingent response does not affect his payoff, so $F$ is a best response there.

There is exactly one subgame perfect equilibrium, $(E,A)$. In the subgame following entry, Bob strictly prefers $3$ to $1$, so backward induction selects acquiescence; Ann then strictly prefers entering for $3$ to staying out for $2$. The threat supporting $(O,F)$ is not optimal in that one-shot subgame.

For infinite repetition, the paper specifies no discount factor. First take the long-run average payoff convention, with all past actions observed. The feasible payoff set is the convex hullAnn can guarantee $2$ in every stage by staying out; Bob can guarantee at least $3$ in every stage by acquiescing whenever entry occurs. These guarantees are also their minmax payoffs: fighting holds Ann's best possible stage payoff to $2$, and entering holds Bob's best possible stage payoff to $3$.

Therefore the sustainable Nash equilibrium average payoffs are exactly the feasible, weakly individually rational payoffs in a repeated game:This is the closed triangle with vertices $(2,3),(2,6),(3,3)$.

Here is a direct sufficiency argument for this particular game. Choose a publicly known sequence of stage outcomes whose frequencies give the target point. Before any observed deviation, follow that sequence. After an Ann deviation, Bob fights forever, so Ann can thereafter obtain at most $2$ per stage. After a Bob deviation, Ann enters forever, so Bob can thereafter obtain at most $3$ per stage. A finite prefix has no effect on long-run average payoff, so no unilateral deviation improves a target with $a\ge 2,b\ge 3$. Rational frequencies can be implemented periodically; arbitrary real frequencies can be implemented by a deterministic sequence with convergent frequencies. Thus even the weak boundary is covered here. In particular, staying out forever and entry followed by acquiescence forever are sustainable; fighting forever is not.

For discounted payoffs $(1-\delta ){\sum }_{t\ge 0}{\delta }^t{u}_i^t$, the folk theorem for repeated games instead gives the usual patience qualification: every feasible point with $a>2,b>3$ can be sustained for all sufficiently large $\delta <1$. It does not classify the whole region for an unspecified fixed $\delta$. The two one-shot Nash equilibrium outcomes remain sustainable for every $\delta$.^[ref]

Finally consider the particular history-dependent pair in the paper. Initially Bob has never acquiesced, so Ann stays out. That preserves the same condition forever, giving payoffs $(2,6)$. The pair is a Nash equilibrium. Holding Bob's strategy fixed, Ann cannot induce an acquiescence: he fights whenever she enters, and his rule never changes unless he has previously acquiesced. Every entry would give her $1$ instead of $2$, so no unilateral deviation helps. Holding Ann's strategy fixed, Bob never reaches a decision node because she stays out; changing his strategy alone cannot create a history in which he actually acquiesces. Hence he also cannot improve.

This direct argument works for both discounted and long-run average payoffs. The outcome gives Ann exactly her minmax payoff and Bob more than his, so it is compatible with the folk theorem for repeated games. A version requiring strict gains above both minmax payoffs is a sufficient condition, and cannot be used to rule out this boundary example.