Random input helps searching predecessors

A data structure problem consists of the finite sets: D of data, Q of queries, A of query answers, associated with a function f: D x Q → A. The data structure of file X is "static" ("dynamic") if we "do not" ("do") require quick updates as X changes. An important goal is to compactly encode a file X ϵ D, such that for each query y ϵ Q, function f (X, y) requires the minimum time to compute an answer in A. This goal is trivial if the size of D is large, since for each query y ϵ Q, it was shown that f(X,y) requires O(1) time for the most important queries in the literature. Hence, this goal becomes interesting to study as a trade off between the "storage space" and the "query time", both measured as functions of the file size n = \X\. The ideal solution would be to use linear O(n) = O(\X\) space, while retaining a constant O(1) query time. However, if f (X, y) computes the static predecessor search (find largest x ϵ X: x ≤ y), then Ajtai [Ajt88] proved a negative result. By using just n0(1) = [IX]0(1) data space, then it is not possible to evaluate f(X,y) in O(1) time Ay ϵ Q. The proof exhibited a bad distribution of data D, such that Ey∗ ϵ Q (a "difficult" query y∗), that f(X,y∗) requires ω(1) time. Essentially [Ajt88] is an existential result, resolving the worst case scenario. But, [Ajt88] left open the question: do we typically, that is, with high probability (w.h.p.)1 encounter such "difficult" queries y ϵ Q, when assuming reasonable distributions with respect to (w.r.t.) queries and data? Below we make reasonable assumptions w.r.t. the distribution of the queries y ϵ Q, as well as w.r.t. the distribution of data X ϵ D. In two interesting scenarios studied in the literature, we resolve the typical (w.h.p.) query time

On the Transformation Capability of Feasible Mechanisms for Programmable Matter

We study theoretical models of programmable matter systems, consisting of n spherical modules kept together by magnetic or electrostatic forces and able to perform two minimal mechanical operations (movements): rotate and/or slide. The goal is for an initial shape A to transform to some target shape B by a sequence of movements. Most of the paper focuses on transformability (feasibility) questions. When only rotation is available, we prove that deciding whether two given shapes can transform to each other, is in P. Under the additional restriction of maintaining global connectivity, we prove inclusion in PSPACE and explore minimum seeds that can make otherwise infeasible transformations feasible. Allowing both rotations and slidings yields universality: any two connected shapes of the same order can be transformed to each other without breaking connectivity, in O(n2) sequential and O(n) parallel time (both optimal). We finally provide a type of distributed transformation

The Dynamics and Stability of Probabilistic Population Processes

We study here the dynamics and stability of Probabilistic Population Processes, via the differential equations approach. We provide a quite general model following the work of Kurtz [15] for approximating discrete processes with continuous differential equations. We show that it includes the model of Angluin et al. [1], in the case of very large populations. We require that the long-term behavior of the family of increasingly large discrete processes is a good approximation to the long-term behavior of the continuous process, i.e., we exclude population protocols that are extremely unstable such as parity-dependent decision processes. For the general model, we give a sufficient condition for stability that can be checked in polynomial time. We also study two interesting sub cases: (a) Protocols whose specifications (in our terms) are configuration independent. We show that they are always stable and that their eventual subpopulation percentages are actually a Markov Chain stationary distribution. (b) Protocols that have dynamics resembling virus spread. We show that their dynamics are actually similar to the well-known Replicator Dynamics of Evolutionary Games. We also provide a sufficient condition for stability in this case

Deterministic Population Protocols for Exact Majority and Plurality

In this paper we study space-efficient deterministic population protocols for several variants of the majority problem including plurality consensus. We focus on space efficient majority protocols in populations with an arbitrary number of colours C represented by k-bit labels, where k = ceiling (log C). In particular, we present asymptotically space-optimal (with respect to the adopted k-bit representation of colours) protocols for (1) the absolute majority problem, i.e., a protocol which decides whether a single colour dominates all other colours considered together, and (2) the relative majority problem, also known in the literature as plurality consensus, in which colours declare their volume superiority versus other individual colours. The new population protocols proposed in this paper rely on a dynamic formulation of the majority problem in which the colours originally present in the population can be changed by an external force during the communication process. The considered dynamic formulation is based on the concepts studied by D. Angluin et al. and O. Michail et al. about stabilizing inputs and composition of population protocols. Also, the protocols presented in this paper use a composition of some known protocols for static and dynamic majority

Sliding into the Future: Investigating Sliding Windows in Temporal Graphs

Graphs are fundamental tools for modelling relations among objects in various scientific fields. However, traditional static graphs have limitations when it comes to capturing the dynamic nature of real-world systems. To overcome this limitation, temporal graphs have been introduced as a framework to model graphs that change over time. In temporal graphs the edges among vertices appear and disappear at specific time steps, reflecting the temporal dynamics of the observed system, which allows us to analyse time dependent patterns and processes. In this paper we focus on the research related to sliding time windows in temporal graphs. Sliding time windows offer a way to analyse specific time intervals within the lifespan of a temporal graph. By sliding the window along the timeline, we can examine the graph’s characteristics and properties within different time periods. This paper provides an overview of the research on sliding time windows in temporal graphs. Although progress has been made in this field, there are still many interesting questions and challenges to be explored. We discuss some of the open problems and highlight their potential for future research

Walrasian equilibria in markets with small demands

We study the complexity of finding a Walrasian equilibrium in markets where the agents have k-demand valuations. These valuations are an extension of unit-demand valuations where a bundle's value is the maximum of its k-subsets' values. For unit-demand agents, where the existence of a Walrasian equilibrium is guaranteed, we show that the problem is in quasi-NC. For k = 2, we show that it is NP-hard to decide if a Walrasian equilibrium exists even if the valuations are submodular, while for k = 3 the hardness carries over to budget-additive valuations. In addition, we give a polynomial-time algorithm for markets with 2-demand single-minded valuations, or unit-demand valuations

The Price of Stability of Weighted Congestion Games

We give exponential lower bounds on the Price of Stability (PoS) of weighted congestion games with polynomial cost functions. In particular, for any positive integer $d$ we construct rather simple games with cost functions of degree at most $d$ which have a PoS of at least $\varOmega(\Phi_d)^{d+1}$, where $\Phi_d\sim d/\ln d$ is the unique positive root of the equation $x^{d+1}=(x+1)^d$. This almost closes the huge gap between $\varTheta(d)$ and $\Phi_d^{d+1}$. Our bound extends also to network congestion games. We further show that the PoS remains exponential even for singleton games. More generally, we provide a lower bound of $\varOmega((1+1/\alpha)^d/d)$ on the PoS of $\alpha$-approximate Nash equilibria for singleton games. All our lower bounds hold for mixed and correlated equilibria as well. On the positive side, we give a general upper bound on the PoS of $\alpha$-approximate Nash equilibria, which is sensitive to the range $W$ of the player weights and the approximation parameter $\alpha$. We do this by explicitly constructing a novel approximate potential function, based on Faulhaber's formula, that generalizes Rosenthal's potential in a continuous, analytic way. From the general theorem, we deduce two interesting corollaries. First, we derive the existence of an approximate pure Nash equilibrium with PoS at most $(d+3)/2$; the equilibrium's approximation parameter ranges from $\varTheta(1)$ to $d+1$ in a smooth way with respect to $W$. Second, we show that for unweighted congestion games, the PoS of $\alpha$-approximate Nash equilibria is at most $(d+1)/\alpha$. Read More: https://epubs.siam.org/doi/10.1137/18M120788