Samer Hassan

Agent-based modelling and simulation for the analysis of social patterns

Agent-based modelling facilitates the implementation of tools for the analysis of social patterns. This comes from the fact that agent related concepts allow the representation of organizational and behavioural aspects of individuals in a society and their interactions. An agent can characterize an individual with capabilities to perceive and react to events in the environment, taking into account its mental state (beliefs, goals), and to interact with other agents in its social environment. There are already tools to perform agent-based social simulation but these are usually hard to use by social scientists, as they require a good expertise in computer programming. In order to cope with such difficulty, we propose the use of agent-based graphical modelling languages, which can help to specify social systems as multi-agent systems in a more convenient way. This is complemented with transformation tools to be able to analyse and derive emergent social behavioural patterns by using the capabilities of existing simulation platforms. In this way, this framework can facilitate the specification and analysis of complex behavioural patterns that may emerge in social systems.

Friendship Dynamics: Modelling Social Relationships through a Fuzzy Agent-Based Simulation

Social relationships such as friendship and partner choice are ruled by the proximity principle, which states that the more similar two individuals are, the more likely they will become friends. However, proximity, similarity, and friendship are concepts with blurred edges and imprecise grades of membership. This study shows how to simulate these friendship dynamics in an agent-based model that applies fuzzy sets theory to implement agent attributes, rules, and social relationships, explaining the process in detail. Although in principle it may be thought that the use of fuzzy sets theory makes agent-based modelling more elaborated, in practice it saves the modeller from taking some arbitrary decisions on how to use crisp values for representing properties that are inherently fuzzy. The consequences of applying fuzzy sets and operations to define a fuzzy friendship relationship are compared with a simpler implementation, with crisp values. By integrating agent computational models and fuzzy set theory, this paper provides useful insights into scholars and practitioners to tackle the uncertainty inherent to social relationships in a systematic way.

Introducing uncertainty into social simulation: using fuzzy logic for agent-based modelling

Agent-based models are useful to study emergent behaviour in social systems. In general, existing agent models tend to be quite simple, but there are social problems that require the consideration of some aspects with uncertainty as human thinking does. Those characteristics can be addressed by using fuzzy sets theory in the specification of the attributes that describe agents representing individuals, and in the functions that model the evolution of individual change of mind, the relationships among individuals in a social network, the inheritance, and the similarity between individuals. This paper discusses the fuzzification of agent-based models and analyses experimentation results for a specific case of the study of the evolution of human values in a society.

Re-thinking simulation: a methodological approach for the application of data mining in agent-based modelling

Agent-based models informed by empirical data are growing in popularity. Many models make extensive use of collected data for the development, initialisation or validation. In parallel, models are growing in size and complexity, generating large amounts of output data. On the other hand, Data Mining is used to extract hidden patterns from large collections of data using different techniques. This work proposes the intense use of Data Mining techniques for the improvement and development of agent-based models. It presents a methodological approach explaining why and when to use Data Mining, with a formal description of each stage of the corresponding process. This is illustrated with a case study, showing the application of the proposed approach step by step.

Agent-Based Social Modeling and Simulation with Fuzzy Sets

Simple models of agents have been used to study emergent behaviour in social systems. However, when considering the evolution of values in human societies, there is a need for the consideration of more complex agent models, which take into account uncertainty in human thinking. This characteristic can be addressed by using fuzzy logic in the specification of the attributes that describe agents representing individuals, the functions that model the evolution of individual change of mind, the relationships among individuals in a social network, the inheritance, and the similarity between individuals. The introduction of fuzzy logic in the models has improved the results of the simulation.

Mentat: a data-driven agent-based simulation of social values evolution

This work presents an agent based simulation model dealing With the evolution of social values in a 20 year period of the Spanish society, approaching it from Ingleharts theories on the subject. Surveys are taken as input to build the model by following a data-driven approach. This has been formalised in a methodology for introducing microsimulation techniques and importing data from several sources. It handles thousands of heterogeneous agents, which have a life cycle, reproduction patterns and complex social relationship dynamics. Its output is consistent with respect to the ideological, religious and demographic parameters observed in real world surveys. Moreover, several extension modules were designed: fuzzy logic for a smoother behaviour; natural language biographies generation; data mining for pattern finding. Thus, Mentat is proposed as a framework for exploring complexity at different levels in the social process.

Application of Model Driven Techniques for Agent-Based Simulation

Agent-based simulation is being recognized as a useful tool for the study of social systems. It is based on the idea that agents can be used as a good abstraction of members of a society, and by simulating their interactions, observe the emergent behavior. Usually, agent-based models for social simulation are rather simple, but there are more and more works that try to apply this technique for rather complex systems, both in the typology of the agents and their relationships, and in scalability. For this reason, software engineering techniques are required to facilitate the development of agent-based simulation systems. In this sense, it can be useful to consider agent-oriented methodologies, as they cope with these requirements. This work explores the application of a model-driven methodology for the development of MAS, INGENIAS. There are several advantages of this approach. One is the possibility to define specific modeling languages that are conceptually close to the domain-expert, in this case for simulation of social systems. This will facilitate the communication of multidisciplinary teams and, by generating code from models, the social scientist is alleviated from the concerns of programming for a simulation platform. This is illustrated with a case study of urban dynamics.

Mixed Narrative and Dialog Content Planning Based on BDI Agents

There exist various narrative systems, focused on different parts of the complex process of story generation. Some of them are oriented to content planning, and some to sentence planning, with different properties and characteristics. In this paper we propose a system based on BDI agents that generates stories (creating content, performing content planningand simple sentence planning) with narrative parts and dialogs. The content for the story is generated in a multiagent social simulation system, and the content planningis based on rules and a state space search algorithm based on the system representation of the readers perception of the story.

Open Peer-to-Peer Systems over Blockchain and IPFS: an Agent Oriented Framework

In recent years, the increasing concerns around the centralized cloud web services (e.g. privacy, governance, surveillance, security) have triggered the emergence of new distributed technologies, such as IPFS or the Blockchain. These innovations have tackled technical challenges that were unresolved until their appearance. Existing models of peer-to-peer systems need a revision to cover the spectrum of potential systems that can be now implemented as peer-to-peer systems. This work presents a framework to build these systems. It uses an agent-oriented approach in an open environment where agents have only partial information of the system data. The proposal covers data access, data discovery and data trust in peer-to-peer systems where different actors may interact. Moreover, the framework proposes a distributed architecture for these open systems, and provides guidelines to decide in which cases Blockchain technology may be required, or when other technologies may be sufficient.

Participation Inequality in Wikis: A Temporal Analysis Using WikiChron

It is widely accepted that peer production communities show a high level of inequality in the level of participation. Typically, we can observe a power law in the distribution of contributions. However, we argue that participation inequality, and specifically its evolution over time, has been understudied. Previous research has concentrated on large successful projects (e.g. Wikipedia), leaving a gap regarding small or mid-size communities. The wiki ecosystem is highly diverse, and so it may be the participation distribution in the communities and its evolution. The aim of this work is twofold: (1) To show a novel webtool, WikiChron, for the analysis of wiki evolution, with a focus on inequality metrics; (2) To provide relevant cases of comparative analysis that show the diversity of the wiki ecosystem, with examples that are counter-intuitive or contradict existing literature, while reflecting the limits of single-metric studies. We aim to open lines of wiki research which require the use of multiple metrics to study participation inequality.