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17 articles matched your search for the keywords:
Passwords, Policies, Organisation, Security, Authentication

Six Levels of Complexity; a Typology of Processes and Systems

Dietrich Fliedner
Journal of Artificial Societies and Social Simulation 4 (1) 4

Kyeywords: Autopoietic Systems, Energy Flow, Pecos (New Mexico), Process Sequence, Self Organisation
Abstract: A closer examination of the position of processes and systems on a scale of complexity is a precondition for the simulation of (biotic and) social processes and systems. It is possible to distinguish 6 levels: 1st level of complexity: the process takes place mainly between 2 concrete participants (simple movement). Control by the environment, not yet a system (solidum). 2nd level of complexity: the process orders the movements, it is horizontally (temporally) oriented, and passes in each case through 4 stages (movement project). The system is the sum of the elements and orders itself through its elements (equilibrium system). 3rd level of complexity: the process distributes energy (demanded products), it is vertically (between superior and inferior environment, market) oriented and passes in each case through 4 bonding levels (flow process). The system is more than the sum of its elements, it regulates itself as a whole (flow-equilibrium system). 4th level of complexity: the process converts energy into products, it is horizontally (temporally) oriented, and passes in each case through 8 stages (7 by overlapping) (process sequence), it is based on division of labour. Each system organises itself structurally as a whole (non-equilibrium system). 5th level of complexity: the process is vertically (hierarchically) oriented and in each case passes through 8 hierarchical levels (7 by overlapping)(hierarchical process). Each system generates itself structurally by organising its elements and subsystems (hierarchic system). 6th level of complexity: process is horizontally (spatially) oriented, and probably passes 16 spheres (13 by overlapping) in each case (universal process, universal system). Each system within the spheres generates itself materially: autopoiesis.

Responsibility for Societies of Agents

Rosaria Conte and Mario Paolucci
Journal of Artificial Societies and Social Simulation 7 (4) 3

Kyeywords: Responsibility, Agents, Cognitive Modeling, E-Governance, Organisation Theory
Abstract: This paper presents a pre-formal social cognitive model of social responsibility as implying the deliberative capacity of the bearer but not necessarily her decision to act or not. Also, responsibility is defined as an objective property of agents, which they cannot remit at their will. Two specific aspects are analysed: (a) the action of "counting upon" given agents as responsible entities, and (b) the consequent property of accountability: responsibility allows to identify the locus of accountability, that is, which agents are accountable for which events and to what extent. Agents responsible for certain events, and upon which others count, are asked to account or respond for these events. Two types of responsibility are distinguished and their commonalities pointed out: (a) a primary form of responsibility, which is a consequence of mere deliberative power, and (b) a task-based form, which is a consequence of task commitment. Primary responsibility is a relation between deliberative agents and social harms, whether these are intended and believed or not, and whether they are actually caused by the agent or not. The boundaries of responsibility will be investigated, and the conceptual links of responsibility with obligation and guilt will be examined. Task-based responsibility implies task- or role-commitment. Furthermore, individual Vs. shared Vs. collective responsibility are distinguished. Considerations about the potential benefits and utility of the analysis proposed for in the field of e-governance are highlighted. Concluding remarks and ideas for future works are discussed in the final section.

Increasing Learner Retention in a Simulated Learning Network Using Indirect Social Interaction

Rob E.J.R. Koper
Journal of Artificial Societies and Social Simulation 8 (2) 5

Kyeywords: Self-Organisation, Education, Distance Learning, Lifelong Learning, Learning Network
Abstract: A learning network is a network of persons who create, share, support and study units of learning (courses, workshops, lessons, etc.) in a specific knowledge domain. Such networks may consist of a large number of alternative units of learning. One of the problems learners face in a learning network is to select the most suitable path through the units of learning in order to build the required competence in an effective and efficient way. This study explored the use of indirect social interaction to solve this problem. Units of learning that have been completed successfully by other comparable learners are presented to the learners as navigational support. A learning network is simulated in which learners search for, enrol in and study units of learning, subject to a variety of constraints: a) variable quality of the different units of learning, b) disturbance, i.e. interference by priorities other than learning and c) matching errors that occur when the entry requirements of the selected unit of learning do not align with the pre-knowledge of the learner. Two conditions are explored in the network: the selection of units of learning with and without indirect social interaction. It was found that indirect social interaction increases the proportion of learners who attain their required competence in the simulated learning network.

Simulating the Emergence of Task Rotation

Kees Zoethout, Wander Jager and Eric Molleman
Journal of Artificial Societies and Social Simulation 9 (1) 5

Kyeywords: Organisation, Task Rotation, Work Groups, Psychological Theory, Multi Agent Simulation
Abstract: In work groups, task rotation may decrease the negative consequences of boredom and lead to a better task performance. In this paper we use multi agent simulation to study several organisation types in which task rotation may or may not emerge. By looking at the development of expertise and motivation of the different agents and their performance as a function of self-organisation, boredom, and task rotation frequency, we describe the dynamics of task rotation. The results show that systems in which task rotation emerges perform better than systems in which the agents merely specialise in one skill. Furthermore, we found that under certain circumstances, a task that leads to a high degree of boredom was performed better than a task causing a low level of boredom.

Socionic Multi-Agent Systems Based on Reflexive Petri Nets and Theories of Social Self-Organisation

Michael Köhler, Roman Langer, Rolf von Lüde, Daniel Moldt, Heiko Rölke and Rüdiger Valk
Journal of Artificial Societies and Social Simulation 10 (1) 3

Kyeywords: Multi-Agents Systems, Petri Nets, Self-Organisation, Social Theories
Abstract: This contribution summarises the core results of the transdisciplinary ASKO project, part of the German DFG's programme Sozionik, which combines sociologists' and computer scientists' skills in order to create improved theories and models of artificial societies. Our research group has (a) formulated a social theory, which is able to explain fundamental mechanisms of self-organisation in both natural and artificial societies, (b) modelled this in a mathematical way using a visual formalism, and (c) developed a novel multi-agent system architecture which is conceptually coherent, recursively structured (hence non-eclectic) and based on our social theory. The article presents an outline of both a sociological middle-range theory of social self-organisation in educational institutions, its formal, Petri net based model, including a simulation of one of its main mechanisms, and the multi-agent system architecture SONAR. It describes how the theory was created by a re-analysis of some grand social theories, by grounding it empirically, and finally how the theory was evaluated by modelling its concepts and statements.

When Does a Newcomer Contribute to a Better Performance? A Multi-Agent Study on Self-Organising Processes of Task Allocation

Kees Zoethout, Wander Jager and Eric Molleman
Journal of Artificial Societies and Social Simulation 13 (3) 7

Kyeywords: Task Allocation, Group Processes, Psychological Theory, Small Groups, Self-Organisation
Abstract: This paper describes how a work group and a newcomer mutually adapt. We study two types of simulated groups that need an extra worker, one group because a former employee had left the group and one group because of its workload. For both groups, we test three conditions, newcomers being specialists, newcomers being generalists, and a control condition with no newcomer. We hypothesise that the group that needs an extra worker because of its workload will perform the best with a newcomer being a generalist. The group that needs an extra worker because a former employee had left the group, will perform better with a specialist newcomer. We study the development of task allocation and performance, with expertise and motivation as process variables. We use two performance indicators, the performance time of the slowest agent that indicates the speed of the group and the sum of performance of all agents to indicate labour costs. Both are indicative for the potential benefit of the newcomer. Strictly spoken the results support our hypotheses although the differences between the groups with generalists and specialists are negligible. What really mattered was the possibility for a newcomer to fit in.

Group-Level Exploration and Exploitation: A Computer Simulation-Based Analysis

Jennifer Kunz
Journal of Artificial Societies and Social Simulation 14 (4) 18

Kyeywords: Organisational Learning, Experience-Based Learning, Exploration, Exploitation, Knowledge Management, Genetic Algorithms
Abstract: Organisational research has studied the tension between exploration and exploitation for years. In essence, this body of research agrees on the necessity of a balance between explora-tive and exploitative processes to prevent an organisation from falling into a learning trap. Thus, to enhance the active management of this balance in organisations, a deeper theoretical understanding of the factors that influence the development of exploration and exploitation has to be gained. One of the recently discussed factors is the interplay between exploration and exploitation on different organisational levels. This paper picks up this discussion. It pro-vides an in-depth, computer simulation-based analysis of the performance of organisational types with varying degrees of within-group and between-group exploration and exploitation in situations of different degrees of task complexity. The findings indicate that a high share of between-group processes as compared to within-group processes positively influences the organisational performance level and that dependent on task complexity the optimal share of exploration and exploitation varies.

SimPass: Quantifying the Impact of Password Behaviours and Policy Directives on an Organisation's Systems

Karen Renaud and Lewis Mackenzie
Journal of Artificial Societies and Social Simulation 16 (3) 3

Kyeywords: Passwords, Policies, Organisation, Security, Authentication
Abstract: Users are often considered the weakest link in the security chain because of their natural propensity for choosing convenience over safe practice. One area with a vast amount of evidence related to poor user behaviour is that of password management. For example, when hackers gain unauthorised access to public websites, subsequent analysis generally confirms that compromised passwords are to blame. We have a pretty good idea of the extent to which careless behaviour impacts on the individual user's personal security. However, we don't fully understand the impact on the organisation as a whole when such laxity is aggregated across a large number of employees, nor do we know how best to intervene so as to improve the level of protection of critical systems. Current wisdom mandates the use of increasingly draconian policies to curb insecure behaviours but it is clear that this approach has limited effectiveness. Unfortunately, no one really understands how the individual directives contained in these policies impact on the security of the systems in an organisation. Sometimes a mandated tightening of policy can have unexpected side-effects which are not easily anticipated and may indeed prove entirely counterproductive. It would be very difficult to investigate these issues in a real-life environment so here we describe a simulation model, which seeks to replicate a typical organisation, with employee agents using a number of systems over an extended period. The model is configurable, allowing adjustment of particular input parameters in order to reflect different policy dictats so as to determine their impact on the security of the simulated organisation's IT infrastructure. This tool will support security specialists developing policies within their organisations by quantifying the longitudinal impacts of particular rules

Self-Policing Through Norm Internalization: A Cognitive Solution to the Tragedy of the Digital Commons in Social Networks

Daniel Villatoro, Giulia Andrighetto, Rosaria Conte and Jordi Sabater-Mir
Journal of Artificial Societies and Social Simulation 18 (2) 2

Kyeywords: Self-Organisation, Norms, Emergent Behavior, Cognitive Modelling, Artificial Social Systems
Abstract: In the seminal work "An Evolutionary Approach to Norms", Axelrod identified internalization as one of the key mechanisms that supports the spreading and stabilization of norms. But how does this process work? This paper advocates a rich cognitive model of different types, degrees and factors of norm internalization. Rather than a none-or-all phenomenon, we claim that norm internalization is a dynamic process, whose deepest step occurs when norms are complied with thoughtlessly. In order to implement a theoretical model of internalization and check its effectiveness in sustaining social norms and promoting cooperation, a simulated web-service distributed market has been designed, where both services and agents' tasks are dynamically assigned. Internalizers are compared with agents whose behaviour is driven only by self-interested motivations. Simulation findings show that in dynamic unpredictable scenarios, internalizers prove more adaptive and achieve higher level of cooperation than agents whose decision-making is based only on utility calculation.

Effort, Satisfaction and Outcomes in Organisations

Marta Posada, Celia Martín-Sierra and Elena Perez
Journal of Artificial Societies and Social Simulation 20 (2) 9

Kyeywords: Effort-Performance, Satisfaction, Organisational Culture, Organizational Structures, Turnover, Human Resource Management Practices
Abstract: In this paper, an agent-based model of bounded-rational agents, who adapt both their effort intensity (by the interaction with other employees) and their stay-on-the-job-intention (by the alignment of their personal values with the Human-Resource Management (HRM) practices implemented by the organisation), is proposed. Our aim is to analyse: (i) the emergence of an organisational culture and its relationship with both formal organisational structures and employees' effort-behaviours; (ii) the increase of organisational performance by retaining valuable-performance employees whereas poor-performance employees are dismissed. We have obtained that: (i) Some possible combinations of both employees-effort behaviours and formal organisational structures can favour the emergence of organisational cultures more than others; (ii) The interaction between employees within matrix structures (balanced or strong) with a democratic team leadership favour the emergence of organisational cultures; (iii) High-effort managers are relevant for the emergence of high-performance organisational cultures; (iv) Turnover (voluntary or involuntary) affects to the emergence of organisational culture negatively. We conclude that the main challenge is to retain high effort managers by adapting the set of HRM practices to them.

Agent-Based Modelling to Assess Community Food Security and Sustainable Livelihoods

Samantha Dobbie, Kate Schreckenberg, James G Dyke, Marije Schaafsma and Stefano Balbi
Journal of Artificial Societies and Social Simulation 21 (1) 9

Kyeywords: Social-Ecological Systems, Livelihood Trajectories, Nutrition, Malawi, Food Security
Abstract: We present a methodological approach for constructing an agent-based model (ABM) to assess community food security and variation among livelihood trajectories, using rural Malawi as a case study. The approach integrates both quantitative and qualitative data to explore how interactions between households and the environment lead to the emergence of community food availability, access, utilisation and stability over time. Results suggest that livelihoods based upon either non-agricultural work or farming are most stable over time, but agricultural labourers, dependent upon the availability of casual work, demonstrate limited capacity to ‘step-up’ livelihood activities. The scenario results suggest that population growth and increased rainfall variability are linked to significant declines in food utilisation and stability by 2050. Taking a systems approach may help to enhance the sustainability of livelihoods, target efforts and promote community food security. We discuss transferability of the methodological approach to other case studies and scenarios.

Model of Knowledge Transfer Within an Organisation

Agnieszka Kowalska-Styczeń, Krzysztof Malarz and Kamil Paradowski
Journal of Artificial Societies and Social Simulation 21 (2) 3

Kyeywords: Knowledge Transfer, Complex Systems, Organisations as Complex Systems, Cellular Automata
Abstract: Many studies show that the acquisition of knowledge is the key to build competitive advantage of companies. We propose a simple model of knowledge transfer within the organisation and we implement the proposed model using cellular automata technique. In this paper the organisation is considered in the context of complex systems. In this perspective, the main role in organisation is played by the network of informal contacts (informal communication). The goal of this paper is to check which factors influence the efficiency and effectiveness of knowledge transfer. Our studies indicate a significant role of initial distribution of chunks of knowledge for knowledge transfer process, and the results suggest taking action in the organisation to shorten the distance (social distance) between people with different levels of knowledge, or working out incentives to share knowledge.

A Dynamic Sustainability Analysis of Energy Landscapes in Egypt: A Spatial Agent-Based Model Combined with Multi-Criteria Decision Analysis

Mostafa Shaaban, Jürgen Scheffran, Jürgen Böhner and Mohamed S. Elsobki
Journal of Artificial Societies and Social Simulation 22 (1) 4

Kyeywords: Energy Security, Energy Landscape, Egypt, Multi-Criteria Decision Analysis, Agent-Based Modeling, Geographic Information System
Abstract: To respond to the emerging challenge of climate change, feasible strategies need to be formulated towards sustainable development and energy security on a national and international level. Lacking a dynamic sustainability assessment of technologies for electricity planning, this paper fills the gap with a multi-criteria and multi-stakeholder evaluation in an integrated assessment of energy systems. This allows to select the most preferred strategies for future planning of energy security in Egypt, with a focus on alternative energy pathways and a sustainable electricity supply mix up to 2100. A novel prototype model is used to integrate multi-criteria decision analysis (MCDA) as a premium decision support approach with agent-based modeling (ABM). This tool is popular in analyzing dynamic complex systems. A GIS-based spatial ABM analyzes future pathways for energy security in Egypt, depending on the preferences of agents for selected criteria to facilitate the transformation of energy landscapes. The study reveals significant temporal variations in the spatial ranking of technologies between actors in the energy sector over this period. We conclude that in order to attain a sustainable energy landscape, we should involve relevant stakeholders and analyze their interactions while considering local spatial conditions and key dimensions of sustainable development.

A Novel Computational Model of the Wheat Global Market with an Application to the 2010 Russian Federation Case

Gianfranco Giulioni, Edmondo Di Giuseppe, Piero Toscano, Francesco Miglietta and Massimiliano Pasqui
Journal of Artificial Societies and Social Simulation 22 (3) 4

Kyeywords: Wheat International Trade, Wheat Price-Quantity Modeling, Food Security, Wheat Price Volatility, Export Ban
Abstract: In this paper, we build a computational model for the analysis of international wheat spot price formation, its dynamics and the dynamics of quantities traded internationally. The model has been calibrated using FAOSTAT data to evaluate its in-sample predictive power. The model is able to generate wheat prices in twelve international markets and traded wheat quantities in twenty-four world regions. The time span considered is from 1992 to 2013. In our study, particular attention was paid to the impact of the Russian Federation's 2010 grain export ban on wheat price and quantities traded internationally. Among other results, we found that the average weighted world wheat price in 2013 would have been 3.55% lower than the observed one if the Russian Federation had not imposed the export ban in 2010.

Understanding the Effects of China’s Agro-Environmental Policies on Rural Households’ Labor and Land Allocation with a Spatially Explicit Agent-Based Model

Ying Wang, Qi Zhang, Srikanta Sannigrahi, Qirui Li, Shiqi Tao, Richard Bilsborrow, Jiangfeng Li and Conghe Song
Journal of Artificial Societies and Social Simulation 24 (3) 7

Kyeywords: Spatially Explicit Agent-Based Model, Social-Ecological Systems, Land Use, Labor Allocation, Agro-Environmental Policies
Abstract: Understanding household labor and land allocation decisions under agro-environmental policies is challenging due to complex human-environment interactions. Here, we developed a spatially explicit agent-based model based on spatial and socioeconomic data to simulate households’ land and labor allocation decisions and investigated the impacts of two forest restoration and conservation programs and one agricultural subsidy program in rural China. Simulation outputs revealed that the forest restoration program accelerates labor out-migration and cropland shrink, while the forest conservation program promotes livelihood diversification via increasing non-farm employment. Meanwhile, the agricultural subsidy program keeps labor for cultivation on land parcels with good quality, but appears less effective for preventing marginal croplands from being abandoned. The policy effects on labor allocation substantially differ between rules based on bounded rational and empirical knowledge of defining household decisions, particularly on sending labor out-migrants and engaging in local off-farm jobs. Land use patterns showed that the extent to which households pursue economic benefits through shrinking cultivated land is generally greater under bounded rationality than empirical knowledge. Findings demonstrate nonlinear social-ecological impacts of the agro-environmental policies through time, which can deviate from expectations due to complex interplays between households and land. This study also suggests that the spatial agent-based model can represent adaptive decision-making and interactions of human agents and their interactions in dynamic social and physical environments.

The Dynamical Relation Between Individual Needs and Group Performance: A Simulation of the Self-Organising Task Allocation Process

Shaoni Wang, Kees Zoethout, Wander Jager and Yanzhong Dang
Journal of Artificial Societies and Social Simulation 24 (4) 9

Kyeywords: Individual Needs, Motivation, Group Performance, Self-Organisation, Task Allocation, Agent-Based Modelling
Abstract: Team performance can be considered a macro-level outcome that depends on three sets of micro-level factors: individual workers contributing to the task, team composition, and task characteristics. For a number of reasons, the complex dynamics between individuals in the task allocation process are difficult to systematically explore in traditional experimental settings: the motivational dynamics, the complex dynamics of task allocation processes, and the lack of experimental control over team composition imply an ABM-approach being more feasible. For this reason, we propose an updated version of the WORKMATE model that has been developed to explore the dynamics of team performance. In doing so, we added Deci and Ryan’s SDT theory, stating that people are motivated by three psychological needs, competence, autonomy, and belongingness. This paper is aimed at explaining the architecture of the model, and some first simulation runs as proof of concept. The experimental results show that: 1) an appropriate motivation threshold will help the team have the lowest performance time; 2) the time needed for the task allocation process is related to the importance of different motivations; 3) highly satisfied teams are more likely composed of members valuing autonomy.

PolicySpace2: Modeling Markets and Endogenous Public Policies

Bernardo Alves Furtado
Journal of Artificial Societies and Social Simulation 25 (1) 8

Kyeywords: Public Policies, Real Estate Market, Agent-Based Modeling, Simulation, Spatial Analysis, Metropolitan Regions
Abstract: Policymakers' role in decision making on alternative policies is facing restricted budgets and an uncertain future. The need to decide on priorities and handle effects across policies has made their task even more difficult. For instance, housing policies involve heterogeneous characteristics of the properties themselves and the intricacy of housing markets within the spatial context of cities. Here, we have proposed PolicySpace2 (PS2) as an adapted and extended version of the open source PolicySpace agent-based model. PS2 is a computer simulation that relies on empirically detailed spatial data to model real estate, along with labor, credit, and goods and services markets. Interaction among workers, firms, a bank, households and municipalities follow the literature benchmarks by integrating economic, spatial and transport research. PS2 is applied here as a comparison of three competing public policies aimed at reducing inequality and alleviating poverty: (a) house acquisition by the government and distribution to lower income households, (b) rental vouchers and (c) monetary aid. Within the model context, monetary aid, that is smaller amounts of help for a larger number of households, improves the economy in terms of production, consumption, reduction of inequality and maintenance of financial duties. PS2 is also a framework that can be further adapted to a number of related research questions.