Choice of optimization routine for multi-agent models: A case of viral video marketing campaign

Very few agent-base computational models are optimized because the usually used optimization routine, the genetic algorithm, is extremely time-consuming. This paper explores how much precision is lost if a simpler optimization routine, mutational hill climber, is used instead. It shows on the case of a viral-video marketing model that even though the standard genetic algorithm is slightly more precise, the mutation hill climbing could be used as an approximate optimization routine for robustness check and scenario analysis.Jen málo multiagentových modelů je optimalizováno, protože obvykle užívaná optimalizační rutina, genetické algoritmy, jsou extrémně výpočetně náročné. Tento článek zkoumá, jak velká část přesnosti se ztratí, pokud je použita jednodušší optimalizační rutina, mutational hill climber. Článek ukazuje na příkladu virální video-marketingové kampaně, že ačkoli je standardní genetický algoritmus poněkud přesnější, mutation hill climbing může být použit jako přibližná optimalizační rutina pro ověření robustnosti a analýzu scénářů.Very few agent-base computational models are optimized because the usually used optimization routine, the genetic algorithm, is extremely time-consuming. This paper explores how much precision is lost if a simpler optimization routine, mutational hill climber, is used instead. It shows on the case of a viral-video marketing model that even though the standard genetic algorithm is slightly more precise, the mutation hill climbing could be used as an approximate optimization routine for robustness check and scenario analysis

Search for the optimal strategy to spread a viral video: An agent-based model optimized with genetic algorithms

Agent-based computational papers on viral marketing have been so far focused on the study of the word-of-mouth knowledge diffusion that merges the decisions to adopt a product and to share information about it. This approach is not suitable for the analysis of the viral video sharing because it is shared with no regard whether the sender has adopted the advertised product or not. This paper presents a more realistic model of viral video diffusion in which every agent that viewed the video shares it once with a random subset of her neighbors. The optimal seeding strategy is then searched with genetic algorithms. The seeding strategy found by the genetic algorithm includes into the initial seed the agents with most connections and lowest clustering ratios; some agents are also selected randomly. However, this complex seeding strategy does not perform significantly better than a simple strategy of selecting agents with many connections.Články popisující multiagentové simulační modely virálního marketingu se dosud zaměřovaly na studium "word-of-mouth" šíření znalosti o produktu, které spojuje rozhodnutí koupit produkt a šířit o něm informace. Tento přístup není vhodný pro analýzu šíření virálního videa, protože to je šířeno bez ohledu na to, zda jeho šiřitel zakoupil propagovaný produkt, nebo ne. Příspěvek prezentuje realističtější model šíření virálního videa, ve kterém každý agent, který video shlédl, jej právě jednou rozešle náhodné podmnožině svých sousedů. Optimální strategie volby agentů, kterým marketer sám na začátku pošle video, je hledána pomocí genetických algoritmů. Optimální strategie nalezená pomocí genetického algoritmu na počátku oslovuje agenty, kteří mají nejvíce spojení a nejnižší clustering ratios; někteří agenti jsou také vybíráni náhodně. Nicméně, tato komplexní strategie nepodává výrazně lepší výsledky než jednoduchá strategie volby agentů s mnoha vazbami.Agent-based computational papers on viral marketing have been so far focused on the study of the word-of-mouth knowledge diffusion that merges the decisions to adopt a product and to share information about it. This approach is not suitable for the analysis of the viral video sharing because it is shared with no regard whether the sender has adopted the advertised product or not. This paper presents a more realistic model of viral video diffusion in which every agent that viewed the video shares it once with a random subset of her neighbors. The optimal seeding strategy is then searched with genetic algorithms. The seeding strategy found by the genetic algorithm includes into the initial seed the agents with most connections and lowest clustering ratios; some agents are also selected randomly. However, this complex seeding strategy does not perform significantly better than a simple strategy of selecting agents with many connections

ConTeXt

summary:Hardly any TeX user makes use of TeX in its "native" form as presented by the initex and virtex programs. Instead, a particular format-macro package, prepared by someone in order to make his or her work easier, is made use of. Nowadays there are two such formats which are mainly used in the Czech Republic: plain TeX and LaTeX. In the near future one more format could join them: ConTeXt. And not only join but maybe even displace LaTeX from its dominant position. In order to make it happen the author wishes to get you acquainted with ConTEXt in this contribution

Do R&D Subsidies Support Innovation or Imitation? Evidence from Four EU Countries

This paper presents an empirical analysis of the effects of public R&D subsidies on the innovative activities of private firms in Bulgaria, the Czech Republic, Germany, and Portugal. We investigate whether public R&D subsidies make firms’ activities more innovative. We measure these effects using firm-level data from the 2010 and 2012 Community Innovation Survey and estimated the effects by propensity score matching. We find that the subsidies do not fully crowd out private sources of R&D expenditure in any of these countries. However, there is a substantial heterogeneity in the impact of the subsidies on firms’ innovativeness. R&D subsidies do support true innovations in the Czech Republic and Germany, but they enhance only imitations in Bulgaria and Portugal.Tento příspěvek představuje empirickou analýzu dopadů veřejných dotací na výzkum a vývoj na inovační aktivity soukromých firem v Bulharsku, České republice, Německu a Portugalsku. Zkoumáme, zda veřejné dotace na výzkum a vývoj motivují firmy přicházet na trh s inovativnějšími produkty. Tyto efekty měříme pomocí dat z Community Innovation Survey za rok 2010 a 2012 a odhadujeme pomocí neparametrického matchingového estimátoru. Zjistili jsme, že dotace v žádné z těchto zemí zcela nevytěsňují soukromé zdroje výdajů na výzkum a vývoj. Existuje však značná heterogenita v dopadu dotací na inovativnost firem. Dotace v oblasti výzkumu a vývoje podporují skutečné inovace v České republice a Německu, ale financují pouze imitace v Bulharsku a Portugalsku

Long-distance rail in Europe: Comparing the forms of head-on competition across Europe

Europe is finally entering a season of liberalisation in the long-distance rail passenger market, which takes the form of on-track competition among public and private operators. The paper provides a broad-scope comparison of relevant European markets, belonging to liberalised and non-liberalised countries, aiming to point out the patterns in terms of supply, competition model and prices. The paper is based on a sample of heterogeneous 69 city-pairs, analysed in two fourteen days periods in 2019 (May/June and November). All available modes are observed, collecting info on companies, frequency of services, and cheapest price. The analysis starts from a schematisation of different business models, based on literature. Then, using the database, we study the country's supply structure, size, and level of intermodal and intra-modal competition through HHIs. Prices are analysed in two steps: the average prices and the price dispersion, searching for their main determinants, including but not limited to competition. Results show that a higher competition level is not always corresponding to low prices, which are instead determined by many other factors such as size of market, demand, socio-economic characteristics, subsidies, production costs, speed advantage, strength of the incumbent, etc. The competition level, instead, directly influences the quality, the supplied capacity, and the price dispersion

Impact of yacon landraces cultivated in the Czech Republic and their ploidy on the short- and long-chain fructooligosaccharides content in tuberous roots

Fructooligosaccharides (FOS) are important tuberous root constituents of yacon (Smallanthus sonchifolius) with beneficial nutritional and prebiotic effects on human health. That is why landraces originally cultivated in Andes are explored with the aim to obtain new ones with high FOS content. In this study eighteen octoploid andfive dodecaploid landraces were for thefirst time evaluated in terms of their tuberous root contents of short-chain fructooligosaccharides GF3-GF10 (Sc-FOS) and long-chain fruc-tooligosaccharides >GF10 (Lc-FOS) by high performance anion exchange chromatography with pulsed amperometric detection (HPAE-PAD). Significant differences between individual landraces were found; eleven of them contained high Sc-FOS and Lc-FOS, whilst twelve showed low Lc-FOS contents. Com-parison of octoploid and dodecaploid groups showed that degree of ploidy level can affect FOS content and the distribution according to degree of polymerisation. High correlations between the contents of Sc-FOS, Lc-FOS and total carbohydrates (r 2 ¼0.97,r 2 ¼0.98 andr 2 ¼0.95, respectively) have been found