Environment design for emerging artificial societies

The NewTies project is developing a system in which societies of agents are expected to develop autonomously as a result of individual, population and social learning. These societies are expected to be able to solve the environmental challenges that they are set by acting collectively. The challenges are intended to be analogous to those faced by early, simple, small-scale human societies. Some issues in the construction of a virtual environment for the system are described and it is argued that multi-agent social simulation has so far tended to neglect the importance of environment design.agent-based modelling, stone age economics, economic anthropolgy

Comparison between purely statistical and multi-agent based approaches for occupant behaviour modeling in buildings

National audienceThis paper analyzes two modeling approaches for occupant behaviour in buildings. It compares a purely statistical approach with a multi-agent social simulation based approach. The study concerns the door openings in an office.Ce papier analyse deux approches de modélisation du comportement d'occupants dans le bâtiment. Il compare une approche purement statistique avec une approche basée sur la simulation sociale dans un environnement multi-agent. L'étude concerne les ouvertures de porte dans un bureau

Pricing the Cloud: An Adaptive Brokerage for Cloud Computing

Abstract—Using a multi-agent social simulation model to predict the behavior of cloud computing markets, Rogers & Cliff (R&C) demonstrated the existence of a profitable cloud brokerage capable of benefitting cloud providers and cloud consumers alike. Functionally similar to financial market brokers, the cloud broker matches provider supply with consumer demand. This is achieved through options, a type of derivatives contract that enables consumers to purchase the option, but not the obligation, of later purchasing the underlying asset—a cloud computing virtual machine instance—for an agreed fixed price. This model benefits all parties: experiencing more predictable demand, cloud providers can better optimize their workflow to minimize costs; cloud users access cheaper rates offered by brokers; and cloud brokers generate profit from charging fees. Here, we replicate and extend the simulation model of R&C using CReST—an opensource, discrete event, cloud data center simulation modeling platform developed at the University of Bristol. Sensitivity analysis reveals fragility in R&C’s model. We address this by introducing a novel method of autonomous adaptive thresholding (AAT) that enables brokers to adapt to market conditions without requiring a priori domain knowledge. Simulation results demonstrate AAT’s robustness, outperforming the fixed brokerage model of R&C under a variety of market conditions. We believe this could have practical significance in the real-world market for cloud computing. Keywords—CReST; simulation; cloud computing; brokerage I

Social Simulation of Stock Markets: Taking It to the Next Level

This paper studies the use of social simulation in linking micro level investor behaviour and macro level stock market dynamics. Empirical data from a survey on individual investors\' decision-making and social interaction was used to formalize the trading and interaction rules of the agents of the artificial stock market SimStockExchange. Multiple simulation runs were performed with this artificial stock market, which generated macro level results, like stock market prices and returns over time. These outcomes were subsequently compared to empirical macro level data from real stock markets. Partial qualitative as well as quantitative agreement between the simulated asset returns distributions and the asset returns distributions of the real stock markets was found.Agent-Based Computational Finance, Artificial Stock Markets, Behavioral Finance, Micro-Macro Links, Multi-Agent Simulation, Stock Market Characteristics

Understanding dynamics of polarization via multiagent social simulation

It is widely recognized that the Web contributes to user polarization, and such polarization affects not just politics but also peoples’ stances about public health, such as vaccination. Understanding polarization in social networks is challenging because it depends not only on user attitudes but also their interactions and exposure to information. We adopt Social Judgment Theory to operationalize attitude shift and model user behavior based on empirical evidence from past studies. We design a social simulation to analyze how content sharing affects user satisfaction and polarization in a social network. We investigate the influence of varying tolerance in users and selectively exposing users to congenial views. We find that (1) higher user tolerance slows down polarization and leads to lower user satisfaction; (2) higher selective exposure leads to higher polarization and lower user reach; and (3) both higher tolerance and higher selective exposure lead to a more homophilic social network

Modelação computacional baseada em agentes : enfrentar a complexidade

A análise dos sistemas sociais e dinâmicos assiste a uma mudança de paradigma, dos métodos matemáticos tradicionais para a simulação baseada em agentes. Trata-se de uma nova linha de pensar, interdisciplinar, onde abundam inovações metodológicas e conceptuais, e onde se criam sociedades artificiais com agentes individuais e inteligentes que se comportam como seres humanos muito simples e plausíveis. Neste artigo abordam-se os modelos desses agentes e os modos como regras simples de interacção social local geram explicações de comportamentos complexos. Através de dois exemplos (inovação tecnológica num parque de ciência e desenho de políticas de tributação), mostra-se como as ferramentas Swarm e NetLogo foram exploradas para modelar os mundos reais.The analysis of social and dynamical systems faces a paradigm shift, from mathematical methods to agent-based simulation. It is a new line of thinking, multidisciplinary, where technological and conceptual innovations grow, and where artificial societies of individual and intelligent agents are generated to replicate simple and plausible human beings. This paper deals with agent models and the ways how simple rules of social interaction grow explanations of complex behaviors. Through two examples (technological innovation in a science park and design of tax compliance policies) we show how Swarm and NetLogo tools were explored to model real worlds.peerreviewe

MECA: A Multi-agent Environment for Cognitive Agents

Many fully functional multi-agent systems have been developed and put to use over the past twenty years, but few of them have been developed to succesfully facilitate social research through the use of social agents. There are three important difficulties that must be dealt with to successfully create a social system for use in social research. First, the system must have an adaptable agent framework that can successfully make intuitive and deliberative decisions much like a human participant would. Secondly, the system must have a robust architecture that not only ensures its functioning no matter the simulation, but also provides an easily understood interface that researchers can interact with while running their simulations. Finally, the system must be effectively distributed to handle the necessary number of agents that social research requires to obtain meaningful results. This paper presents our work on creating a multi-agent simulation for social agents that overcomes these three difficulties