Agent-based Models in Supporting Pedestrian Transportation Planning and Design

Agent-based models offer a new approach to understanding human-urban interactions in transportation systems, allowing individual entities within a system to be characterized with cognitive and behavioral properties. This paper discussed the role of agent-based representations of pedestrian transportation systems, detailing the underlying assumptions and techniques behind different types of pedestrian models and illustrating the differences between aggregate and individual agent representations. It then turns attention to the case study and the development of a cognitive pedestrian model as a way to illustrate the spectrum of potential spatial behaviors that are enabled by material changes to the transportation network. The paper concludes with a discussion and specific frameworks for employing agent-based models to support transportation planning decisions

A computation trust model with trust network in multi-agent systems

Trust is a fundamental issue in multi-agent systems, especially when they are applied in e-commence. The computational models of trust play an important role in determining who and how to interact in open and dynamic environments. To this end, a computation trust model is proposed in which the confidence information based on direct prior interactions with the target agent and the reputation information from trust network are used. In this way, agents can autonomously deal with deception and identify trustworthy parties in multi-agent systems. The ontological property of trust is also considered in the model. A case study is provided to show the effectiveness of the proposed model. <br /

Social Influences in Opinion Dynamics: the Role of Conformity

We study the effects of social influences in opinion dynamics. In particular, we define a simple model, based on the majority rule voting, in order to consider the role of conformity. Conformity is a central issue in social psychology as it represents one of people's behaviors that emerges as a result of their interactions. The proposed model represents agents, arranged in a network and provided with an individual behavior, that change opinion in function of those of their neighbors. In particular, agents can behave as conformists or as nonconformists. In the former case, agents change opinion in accordance with the majority of their social circle (i.e., their neighbors); in the latter case, they do the opposite, i.e., they take the minority opinion. Moreover, we investigate the nonconformity both on a global and on a local perspective, i.e., in relation to the whole population and to the social circle of each nonconformist agent, respectively. We perform a computational study of the proposed model, with the aim to observe if and how the conformity affects the related outcomes. Moreover, we want to investigate whether it is possible to achieve some kind of equilibrium, or of order, during the evolution of the system. Results highlight that the amount of nonconformist agents in the population plays a central role in these dynamics. In particular, conformist agents play the role of stabilizers in fully-connected networks, whereas the opposite happens in complex networks. Furthermore, by analyzing complex topologies of the agent network, we found that in the presence of radical nonconformist agents the topology of the system has a prominent role; otherwise it does not matter since we observed that a conformist behavior is almost always more convenient. Finally, we analyze the results of the model by considering that agents can change also their behavior over time.Comment: 22 pages, 12 figures, appears in Physica A: Statistical Mechanics and its Applications (volume 414) 201

Empirical agent-based modelling of everyday pro-environmental behaviours at work

We report on agent-based modelling work in the LOCAW project (Low Carbon at Work: Modelling Agents and Organisations to Achieve Transition to a Low Carbon Europe). The project explored the effectiveness of various backcasting scenarios conducted with case study organisations in bringing about pro-environmental change in the workforce in the domains of transport, energy use and waste. The model used qualitative representations of workspaces in formalising each scenario, and decision trees learned from questionnaire responses to represent decision-making. We describe the process by which the decision trees were constructed, noting that the use of decision trees in agent-based models requires particular considerations owing to the potential use of explanatory variables in model dynamics. The results of the modelling in various scenarios emphasise the importance of structural environmental changes in facilitating everyday pro-environmental behaviour, but also show there is a role for psychological variables such as norms, values and efficacy. As such, the topology of social interactions is a potentially important driver, raising the interesting prospect that both workplace geography and organisational hierarchy have a role to play in influencing workplace pro-environmental behaviours

The fate of bilingualism in a model of language competition

The original publication is available at Springer website: http://www.springer.com/computer/mathematics/book/978-4-431-73150-4.In the general context of dynamics of social consensus, we study an agent based model for the competition between two socially equivalent languages, addressing the role of bilingualism and social structure. In a regular network, we study the formation of linguistic domains and their interaction across the boundaries. We analyse also a small world social structure, in order to capture the effect of long range social interactions. In both cases, a final scenario of dominance of one language and extinction of the other is obtained, but with smaller times for extinction in the latter case. In addition, we compare our results to our previous work on the agent based version of Abrams-Strogatz model.We acknowledge financial support from the MEC (Spain) through project CONOCE2 (FIS2004-00953). X. C. also acknowledges financial support from a Ph.D. fellowship of the Govern de les Illes Balears (Spain). L. L-P. also acknowledges financial support from the Autonomous Government of Galicia (PGIDIT05PXIC20401PN), and the MEC (Spain) and the ERDF (HUM2004-00940).http://dx.doi.org/10.1007/978-4-431-73167-

The Influence of Financial Benefits and Peer Effects on the Adoption of Residential Rooftop Photovoltaic Systems

The uptake of residential photovoltaic systems is essential for energy system transformation towards carbon neutrality and decentralization. However, despite numerous campaigns to incentivize their uptake, adoption by residential homeowners is lacking behind. While countless drivers and barriers have been identified, the decision process is not fully understood. To address this gap, we developed an agent-based residential rooftop photovoltaic adoption model called PVact. Our model analyzes the interactions of potential household adopters based on their utility functions and social network, with a focus on the role of monetary evaluation and social pressure in adoption behavior. In this paper, we aim to assess the influence of monetary evaluation and social pressure in an abstract case study based on real-world data from the municipality of Leipzig, Germany. We consider stochastic dynamics through scenario analysis to investigate the influence of these factors on adoption behavior. Our results show that monetary evaluation and social pressure have a significant impact on adoption behavior. Specifically, we find shifting adoption patterns with an increased requirement for monetary returns and higher level of normative pressure required for households to act. Higher resistance against these pressure shows more stochastic variations

Adaptive tension, self-organization and emergence : A complex system perspective of supply chain disruptions

The purpose of this thesis was to explore how microstate human interactions produce macro level self-organization and emergence in a supply disruption scenario, as well as discover factors and typical human behaviour that bring about disruptions. This study argues that the complex adaptive system’s view of complexity is most suited scholarly foundation for this research enquiry. Drawing on the dissipative structure based explanation of emergence and self-organization in a complex adaptive system, this thesis further argues that an energy gradient between the ongoing and designed system conditions, known as adaptive tension, causes supply chains to self-organize and emerge. This study adopts a critical realist ontology operationalized by a qualitative case research and grounded theory based analysis. The data was collected using repertory grid interviews of 22 supply chain executives from 21 firms. In all 167 cases of supply disruptions were investigated. Findings illustrate that agent behaviours like loss of trust, over ambitious pursuit, use of power and privilege, conspiring against best practices and heedless performance were contributing to disruption. Impacted by these behaviours, supply chains demonstrated impaired disruption management capabilities and increased disruption probability. It was also discovered that some of these system patterns and microstate agent behaviours pushed the supply chains to a zone of emergent complexity where these networks self-organized and emerged into new structures or embraced changes in prevailing processes or goals. A conceptual model was developed to explain the transition from micro agent behaviour to system level self-organization and emergence. The model described alternate pathways of a supply chain under adaptive tension. The research makes three primary research contributions. Firstly, based upon the theoretical model, this research presents a conceptualization of supply chain emergence and self-organization from dissipative structures and adaptive tension based view of complexity. Secondly, it formally introduces and validates the role of behavioural and cognitive element of human actions in a supply chain scenario. Lastly, it affirms the complex adaptive system based conceptualization of supply chain networks. These contributions succeed in providing organizations with an explanation for observed deviations in their operations performance using a behavioural aspect of human agents

OpenKnowledge at work: exploring centralized and decentralized information gathering in emergency contexts

Real-world experience teaches us that to manage emergencies, efficient crisis response coordination is crucial; ICT infrastructures are effective in supporting the people involved in such contexts, by supporting effective ways of interaction. They also should provide innovative means of communication and information management. At present, centralized architectures are mostly used for this purpose; however, alternative infrastructures based on the use of distributed information sources, are currently being explored, studied and analyzed. This paper aims at investigating the capability of a novel approach (developed within the European project OpenKnowledge1) to support centralized as well as decentralized architectures for information gathering. For this purpose we developed an agent-based e-Response simulation environment fully integrated with the OpenKnowledge infrastructure and through which existing emergency plans are modelled and simulated. Preliminary results show the OpenKnowledge capability of supporting the two afore-mentioned architectures and, under ideal assumptions, a comparable performance in both cases

Analysis and design of multiagent systems using MAS-CommonKADS

This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADSwith techniquesfrom objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network