
Michail TheofilatosUniversity of Liverpool | UoL · Department of Computer Science
Michail Theofilatos
PhD Student at the University of Liverpool
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16
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Introduction
Skills and Expertise
Publications
Publications (16)
We study a new algorithmic process of graph growth. The process starts from a single initial vertex \(u_0\) and operates in discrete time-steps, called slots. In every slot \(t\ge 1\), the process updates the current graph instance to generate the next graph instance \(G_t\). The process first sets \(G_t = G_{t-1}\). Then, for every \(u\in V(G_{t-1...
We examine the problem of gathering [Formula: see text] agents (or multi-agent rendezvous) in dynamic graphs which may change in every round. We consider a variant of the [Formula: see text]-interval connectivity model [9] in which all instances (snapshots) are always connected spanning subgraphs of an underlying graph, not necessarily a clique. Th...
Motivated by biological processes, we introduce here the model of growing graphs, a new model of highly dynamic networks. Such networks have as nodes entities that can self-replicate and thus can expand the size of the network. This gives rise to the problem of creating a target network $G$ starting from a single entity (node). To properly model th...
We study the problems of leader election and population size counting for population protocols: networks of finite-state anonymous agents that interact randomly under a uniform random scheduler. We provide simple protocols for approximate counting of the size of the population and for leader election. We show a protocol for leader election that ter...
We examine the problem of gathering $k \geq 2$ agents (or multi-agent rendezvous) in dynamic graphs which may change in every synchronous round but remain always connected ($1$-interval connectivity) [KLO10]. The agents are identical and without explicit communication capabilities, and are initially positioned at different nodes of the graph. The p...
We study Crystal Structure Prediction, one of the major problems in computational chemistry. This is essentially a continuous optimization problem, where many different, simple and sophisticated, methods have been proposed and applied. The simple searching techniques are easy to understand, usually easy to implement, but they can be slow in practic...
We study Crystal Structure Prediction, one of the major problems in computational chemistry. This is essentially a continuous optimization problem, where many different, simple and sophisticated, methods have been proposed and applied. The simple searching techniques are easy to understand, usually easy to implement, but they can be slow in practic...
In this work, we consider adversarial crash faults of nodes in the network constructors model [Michail and Spirakis, 2016]. We first show that, without further assumptions, the class of graph languages that can be (stably) constructed under crash faults is non-empty but small. When there is a finite upper bound f on the number of faults, we show th...
In this work, we consider adversarial crash faults of nodes in the network constructors model $[$Michail and Spirakis, 2016$]$. We first show that, without further assumptions, the class of graph languages that can be (stably) constructed under crash faults is non-empty but small. In particular, if an unbounded number of crash faults may occur, we...
Population protocols [2] are networks that consist of very weak computational entities (also called nodes or agents), regarding their individual capabilities and it has been shown that are able to perform complex computational tasks when they work collectively. Leader Election is the process of designating a single agent as the coordinator of some...
We study the problems of leader election and population size counting for population protocols: networks of finite-state anonymous agents that interact randomly under a uniform random scheduler. We show a protocol for leader election that terminates in $O(\log_m(n) \cdot \log_2 n)$ parallel time, where $m$ is a parameter, using $O(\max\{m,\log n\})...
We study population protocols: networks of anonymous agents that interact under a scheduler that picks pairs of agents uniformly at random. The _size counting problem_ is that of calculating the exact number $n$ of agents in the population, assuming no leader (each agent starts in the same state). We give the first protocol that solves this problem...