1,969 research outputs found
On dynamic monopolies of graphs: the average and strict majority thresholds
Let be a graph and
be an assignment of thresholds to the vertices of . A subset of vertices
is said to be a dynamic monopoly corresponding to if the vertices
of can be partitioned into subsets such that
and for any , each vertex in has at least
neighbors in . Dynamic monopolies are in fact
modeling the irreversible spread of influence in social networks. In this paper
we first obtain a lower bound for the smallest size of any dynamic monopoly in
terms of the average threshold and the order of graph. Also we obtain an upper
bound in terms of the minimum vertex cover of graphs. Then we derive the upper
bound for the smallest size of any dynamic monopoly when the graph
contains at least one odd vertex, where the threshold of any vertex is set
as (i.e. strict majority threshold). This bound
improves the best known bound for strict majority threshold. We show that the
latter bound can be achieved by a polynomial time algorithm. We also show that
is an upper bound for the size of strict majority dynamic
monopoly, where stands for the matching number of . Finally, we
obtain a basic upper bound for the smallest size of any dynamic monopoly, in
terms of the average threshold and vertex degrees. Using this bound we derive
some other upper bounds
On the Voting Time of the Deterministic Majority Process
In the deterministic binary majority process we are given a simple graph
where each node has one out of two initial opinions. In every round, every node
adopts the majority opinion among its neighbors. By using a potential argument
first discovered by Goles and Olivos (1980), it is known that this process
always converges in rounds to a two-periodic state in which every node
either keeps its opinion or changes it in every round.
It has been shown by Frischknecht, Keller, and Wattenhofer (2013) that the
bound on the convergence time of the deterministic binary majority
process is indeed tight even for dense graphs. However, in many graphs such as
the complete graph, from any initial opinion assignment, the process converges
in just a constant number of rounds.
By carefully exploiting the structure of the potential function by Goles and
Olivos (1980), we derive a new upper bound on the convergence time of the
deterministic binary majority process that accounts for such exceptional cases.
We show that it is possible to identify certain modules of a graph in order
to obtain a new graph with the property that the worst-case
convergence time of is an upper bound on that of . Moreover, even
though our upper bound can be computed in linear time, we show that, given an
integer , it is NP-hard to decide whether there exists an initial opinion
assignment for which it takes more than rounds to converge to the
two-periodic state.Comment: full version of brief announcement accepted at DISC'1
Bidding Rings and the Winner's Curse: The Case of Federal Offshore Oil and Gas Lease Auctions
This paper extends the theory of legal cartels to affiliated private value and common value environments, and applies the theory to explain joint bidding patterns in U.S. federal government offshore oil and gas lease auctions. We show that efficient collusion is always possible in private value environments, but may not be in common value environments. In the latter case, fear of the winner's curse can cause bidders not to bid, which leads to inefficient trade. Buyers with high signals may be better off if no one colludes. The bid data is consistent with oil and gas leases being common value assets, and with the prediction that the winner's curse can prevent rings from forming on marginal tracts.
Parameterized Inapproximability of Target Set Selection and Generalizations
In this paper, we consider the Target Set Selection problem: given a graph
and a threshold value for any vertex of the graph, find a minimum
size vertex-subset to "activate" s.t. all the vertices of the graph are
activated at the end of the propagation process. A vertex is activated
during the propagation process if at least of its neighbors are
activated. This problem models several practical issues like faults in
distributed networks or word-to-mouth recommendations in social networks. We
show that for any functions and this problem cannot be approximated
within a factor of in time, unless FPT = W[P],
even for restricted thresholds (namely constant and majority thresholds). We
also study the cardinality constraint maximization and minimization versions of
the problem for which we prove similar hardness results
Searching for the Concentration-Price Effect in the German Movie Theater Industry
This paper investigates whether a price-concentration relationship can be found on local cinema markets in Germany. First, we test a model of monopolistic pricing using a new set of German micro data and find no significant difference in admission prices on monopoly and oligopoly markets. In a next step, we test whether this can be explained by the existence of local monopolies, but find no hint of that. Implicit or explicit collusion among cinema operators might explain our observations.price-concentration study; cinema pricing
On the approximability and exact algorithms for vector domination and related problems in graphs
We consider two graph optimization problems called vector domination and
total vector domination. In vector domination one seeks a small subset S of
vertices of a graph such that any vertex outside S has a prescribed number of
neighbors in S. In total vector domination, the requirement is extended to all
vertices of the graph. We prove that these problems (and several variants
thereof) cannot be approximated to within a factor of clnn, where c is a
suitable constant and n is the number of the vertices, unless P = NP. We also
show that two natural greedy strategies have approximation factors ln D+O(1),
where D is the maximum degree of the input graph. We also provide exact
polynomial time algorithms for several classes of graphs. Our results extend,
improve, and unify several results previously known in the literature.Comment: In the version published in DAM, weaker lower bounds for vector
domination and total vector domination were stated. Being these problems
generalization of domination and total domination, the lower bounds of 0.2267
ln n and (1-epsilon) ln n clearly hold for both problems, unless P = NP or NP
\subseteq DTIME(n^{O(log log n)}), respectively. The claims are corrected in
the present versio
The Power of Small Coalitions under Two-Tier Majority on Regular Graphs
In this paper, we study the following problem. Consider a setting where a
proposal is offered to the vertices of a given network , and the vertices
must conduct a vote and decide whether to accept the proposal or reject it.
Each vertex has its own valuation of the proposal; we say that is
``happy'' if its valuation is positive (i.e., it expects to gain from adopting
the proposal) and ``sad'' if its valuation is negative. However, vertices do
not base their vote merely on their own valuation. Rather, a vertex is a
\emph{proponent} of the proposal if the majority of its neighbors are happy
with it and an \emph{opponent} in the opposite case. At the end of the vote,
the network collectively accepts the proposal whenever the majority of its
vertices are proponents. We study this problem for regular graphs with loops.
Specifically, we consider the class of -regular graphs
of odd order with all loops and happy vertices. We are interested
in establishing necessary and sufficient conditions for the class
to contain a labeled graph accepting the proposal, as
well as conditions to contain a graph rejecting the proposal. We also discuss
connections to the existing literature, including that on majority domination,
and investigate the properties of the obtained conditions.Comment: 28 pages, 8 figures, accepted for publication in Discrete Applied
Mathematic
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