Set function ($f:\mathcal{P}(V)\to \mathbb{R}$)

A real-valued set function assigns a real number to each subset of a specified ground set.

On nonempty subsets of a nonempty finite set $V$, take the maximum of the contained element weights. Setting $f(\varnothing )={\min }_{v\in V}w(v)$ extends this to a monotone set function and a submodular set function. More generally any value at the empty set at most every element weight works, because ${\Delta }_{x}f(S)=\max \{0,w(x)-f(S)\}$ satisfies diminishing returns.

The marginal increment measures how much a set function changes when one new element is added. Usually $x\notin S$ is required; if $x\in S$, the displayed difference is zero. The marginal increments of a modular set function depend only on $x$. The marginal increments of a submodular set function can only decrease as the input subset grows without acquiring $x$.

On a finite ground set, a modular set function is a set function satisfying the displayed equality for every pair of subsets. Equivalently,To prove this representation, apply the equality to disjoint $S$ and $\{x\}$: $h(S+x)-h(S)=h(\{x\})-h(\varnothing )$. Add these fixed marginal increments along any ordering of $S$. Conversely, the contributions of each element and of the constant cancel in the displayed identity. Thus a modular set function need not be a normalised set function; its normalised instances are precisely the real-valued set functions with finite additivity on a finite power set. Adding or subtracting a modular set function preserves submodularity.

A set function on the power set of a ground set $V$ is symmetric when complementary subsets have equal values. A hypergraph cut function has this property because swapping the two sides changes no crossing hyperedge. If a symmetric set function is also a monotone set function, it is constant: $f(\varnothing )\le f(S)\le f(V)=f(\varnothing )$.

A real-valued set function is monotone, in the nondecreasing convention, when enlarging its input subset cannot decrease its value. Equivalently, each marginal increment ${\Delta }_{x}f(S)$ is nonnegative. This follows by adding elements individually; the converse follows by considering $S\subseteq S\cup \{x\}$. A normalised set function with this property is a nonnegative function.

A set function is normalised when its value at the empty set is zero. Subtracting the constant $f(\varnothing )$ normalises any real-valued set function and preserves submodularity and the monotone set function property.

A real-valued set function on an algebra of sets is finitely additive if it has the displayed property for disjoint pairs. It follows that $F(\varnothing )=0$. On a finite ambient set, induction gives $F(A)={\sum }_{x\in A}F(\{x\})$, so arbitrary signed singleton weights describe all such functions. Summing the pointwise indicator function identity for the inclusion-exclusion principle against these weights proves the same formula for $F$.

A real-valued set function is supermodular if it satisfies the displayed inequality. Its negative is a submodular set function. Equivalently, the gain from adding an element cannot decrease as the set grows. This is the defining property of a convex cooperative game, and makes coalition marginal allocations lie in the core of a cooperative game.

A set function is submodular if $f(A)+f(B)\ge f(A\cup B)+f(A\cap B)$ for every pair of subsets. Entropy submodularity is a fundamental example.

Every real-valued submodular set function on a finite ground set $V$ is the sum of a normalised set function $g$ that is nonnegative, monotone and submodular, and a modular set function $h$. A useful explicit choice isProof. The formula makes $h$ a modular set function, so $g$ is a submodular set function. It is a normalised set function because $h(\varnothing )=f(\varnothing )$. For $x\notin S$, diminishing returns gives ${\Delta }_{x}f(S)\ge {\Delta }_{x}f(V\setminus \{x\})=d_x$, hence ${\Delta }_{x}g(S)\ge 0$. Thus $g$ is a monotone set function, and starting at zero makes it a nonnegative function. The decomposition separates all potentially negative terminal marginal increments into the simple additive term. A constant term in $h$ is necessary unless $f$ is already a normalised set function.

Suppose $f$ is a normalised set function and a submodular set function, and $T_1,\dots ,T_t\subseteq T$ cover every element of $T$ exactly $k$ times, counting repetitions in the indexed collection. Then the displayed inequality holds. Neither the monotone set function property nor the nonnegative function property is required.

Proof. Fix an ordering of $T$ and write $a_j=f(P_j)-f(P_{j-1})$ for its successive marginal increments. The chain lower bound for a submodular set function gives $f(T_i)\ge {\sum }_{x_j\in T_i}{a}_j$. Summing counts each $a_j$ exactly $k$ times, and ${\sum }_j{a}_j=f(T)$. Exact coverage matters because the $a_j$ may be negative. For a monotone set function, the same argument also allows each element to occur at least $k$ times.

Let $f$ be a normalised set function that is a submodular set function, and order a finite subset $T=\{x_1,\dots ,x_n\}$. Set $P_j=\{x_1,\dots ,x_j\}$ and $P_0=\varnothing$. Then the displayed inequality holds for every $U\subseteq T$, with equality for $U=T$. The right side is a modular set function lying below $f$ on the power set of $T$ and touching it at the top.

Proof. Reveal the elements of $U$ in the chosen order. Immediately before adding $x_j\in U$, the conditioning set is $U\cap P_{j-1}\subseteq P_{j-1}$. By diminishing returns, its marginal increment is at least $f(P_j)-f(P_{j-1})$. Sum and use $f(\varnothing )=0$. The same telescoping sum gives equality at $T$. The individual increments need not be nonnegative.

For a real-valued set function on a finite ground set, the displayed marginal increment comparison is equivalent to submodularity. The interpretation is that an additional item contributes no more after more items have already been chosen. This concerns relative increments, which may be negative; it does not assert the monotone set function property.

Proof. Applying the defining inequality for a submodular set function to $A+x$ and $B$ gives the comparison immediately. Conversely, list $A\setminus B=\{x_1,\dots ,x_m\}$ and compare adding these elements, in the same order, first to $A\cap B$ and then to $B$. At every step the first conditioning set is contained in the second, so the first marginal increment is at least the second. The telescoping sums givewhich rearranges to submodularity.