How Can Social Networks Ever Become Complex? Modelling the Emergence of Complex Networks from Local Social Exchanges

Small-world and power-law network structures have been prominently proposed as models of large networks. However, the assumptions of these models usually lack sociological grounding. We present a computational model grounded in social exchange theory. Agents search attractive exchange partners in a diverse population. Agent use simple decision heuristics, based on imperfect, local information. Computer simulations show that the topological structure of the emergent social network depends heavily upon two sets of conditions, harshness of the exchange game and learning capacities of the agents. Further analysis show that a combination of these conditions affects whether star-like, small-world or power-law structures emerge.Complex Networks, Power-Law, Scale-Free, Small-World, Agent-Based Modeling, Social Exchange Theory, Structural Emergence

A relação entre capital humano, inovação e internacionalização das micro e pequenas empresas: o caso da fileira agroalimentar do Vale do Tejo

This paper aims to contribute empirically to a better understanding of the relationship between human capital formation in micro and small enterprises and the respective behaviors in innovation and internationalization. Based on a brief review of literature on human capital and regional innovation systems, as well as in results obtained in a survey, the paper reveals that the reduced stock of human capital in this corporate segment can inhibit their potential for innovation; but this does not impede access external markets. There is evidence that these firms make use of stable partnerships with intermediary economic agents and promoting organizations, demonstrating how effective are non-market assets (of territorial nature, specially) to the agri-food supply chain competitiveness of Tagus Valley, in the framework of Common Agricultural Policy.Este artigo visa contribuir empiricamente para uma melhor compreensão da relação entre a formação de capital humano nas micro e pequenas empresas e os respetivos comportamentos em inovação e internacionalização. Baseado numa revisão de literatura sucinta acerca do capital humano e dos sistemas territoriais de inovação, bem como em resultados obtidos num estudo por inquérito, o artigo revela que o reduzido ‘stock’ de capital humano neste segmento de empresas pode inibir o seu potencial de inovação; contudo, tal não impede que alcancem mercados externos. Existe evidência de que estas empresas fazem uso de parcerias estáveis com agentes económicos intermediários e organizações promotoras, demonstrando quão eficazes se revelam os ativos não mercantis (de natureza territorial, especialmente) para a competitividade da fileira agroalimentar do Vale do Tejo, no quadro da Política Agrícola Comum.info:eu-repo/semantics/publishedVersio

Deep Reinforcement Learning from Self-Play in Imperfect-Information Games

Many real-world applications can be described as large-scale games of imperfect information. To deal with these challenging domains, prior work has focused on computing Nash equilibria in a handcrafted abstraction of the domain. In this paper we introduce the first scalable end-to-end approach to learning approximate Nash equilibria without prior domain knowledge. Our method combines fictitious self-play with deep reinforcement learning. When applied to Leduc poker, Neural Fictitious Self-Play (NFSP) approached a Nash equilibrium, whereas common reinforcement learning methods diverged. In Limit Texas Holdem, a poker game of real-world scale, NFSP learnt a strategy that approached the performance of state-of-the-art, superhuman algorithms based on significant domain expertise.Comment: updated version, incorporating conference feedbac