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Contains fulltext : 191881.pdf (publisher's version ) (Closed access), The rapid development and increasing complexity of modern socio-technical systems suggest an urgent need for systemic safety analysis approaches because traditional linear models cannot cope with this complexity. In the aviation safety literature, among systemic accident and incident analysis methods, Systems Theoretic Accident Modelling and Processes (STAMP) and Agent-based modelling (ABM) are the most cited ones. STAMP is a qualitative analysis approach known for its thoroughness and comprehensiveness. Computational ABM approach is a formal quantitative method which proved to be suitable for modelling complex flexible systems. In addition, from a legal point of view, formal systemic institutional modelling potentially provides an interesting contribution to accident and incident analysis. The current work compares three systemic modelling approaches: STAMP, ABM and institutional modelling applied to a case study in an aviation domain.

2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 11-14 August 2014, Item does not contain fulltext

12th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2014, Salamanca, Spain, June 4-6, 2014, Item does not contain fulltext, Aviation incidents often have a complex character in the sense that a number of different aspects of human and technical functioning come together in creating the incident. Usually only model constructs or computational agent models are available for each of these aspects separately. To obtain an overall model, these agent models have to be integrated. In this paper, existing agent models are used to develop a formal, executable agent model of a real-world scenario concerning an aircraft that descends below the minimal descent altitude because of impaired conditions of the flight crew members. Based on the model, a few proof-of-concept simulations are generated that describe how such hazardous scenarios can evolve.

Transactions on Computational Collective Intelligence XVII, Item does not contain fulltext, This paper introduces an agent-based approach to analyze the dynamics of accidents and incidents in aviation. The approach makes use of a number of elements, including formalization of a real world scenario, agent-based simulation of variations of the scenario, and formal verification of dynamic properties against the (empirical and simulated) scenarios. The scenario formalization part enables incident reconstruction and formal analysis of it. The simulation part enables the analyst to explore various hypothetical scenarios under different circumstances, with an emphasis on error related to human factors. The formal verification part enables the analyst to identify scenarios involving potential hazards, and to relate those hazards (via so-called interlevel relations) to inadequate behavior on the level of individual agents. The approach is illustrated by means of a case study on a runway incursion incident, and a number of advantages with respect to the current state-of-the-art are discussed.

2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, 11-14 August 2014, Item does not contain fulltext, This paper compares population-based and agent-based simulation of the dynamics of group Situation Awareness. The question how Situation Awareness spreads among a team of agents is important for numerous applications. In this paper, a population-based and an agent-based model of this process are proposed, and applied to a case study in aviation. A number of relevant simulations of the models are performed, to investigate whether the behaviour of the population-based model can approximate the pattern produced by the agent-based model. It was demonstrated that, especially for larger populations, the dynamics of the agent-based simulations can be approximated by population-based simulations, since both models demonstrate a similar pattern.

Fifth International Conference on Agents and Artificial Intelligence, ICAART'13, Item does not contain fulltext

Fourth International Air Transport and Operations Symposium, Item does not contain fulltext

A healthy lifestyle contributes to better health and helps diminish risks for chronic diseases, such as cardiovascular disease or diabetes. Moreover, people who have already developed a chronic illness often improve or minimize their symptoms by maintaining a healthy lifestyle. Although coaching apps that support people in attaining their healthy goals are plentiful, few are based on known theories of behavior change. Here, the authors introduce the Computerized Behavior Intervention model, which describes formal relations between determinants of behavior change based on psychological theories. The model is the core of the eMate intelligent support system, which tries to determine the reason why the user acts in conflict with his or her health goals. Using a mobile phone app and an online lifestyle diary, the system coaches the user with tailored information and persuasive motivational messages. © 2002-2012 IEEE.

25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Dalian, China, June 9-12, 2012, Item does not contain fulltext, In this paper, a formal, agent-based approach is presented to analyse the dynamics of accidents and incidents in aviation. The approach comprises a number of steps, which include development of domain ontology, formalisation of scenarios, formal specification of dynamic properties, identification of interlevel relations between dynamic properties at different aggregation levels, and automated verification of dynamic properties. The approach is illustrated by means of a case study on a runway incursion incident, and a number of advantages with respect to the current state-of-the-art are discussed.

Human health depends to a large extent on their behavior. Adopting a healthy lifestyle often requires behavior change. This paper presents a computational model of behavior change that describes formal relations between the determinants of behavior change, based on existing psychological theories. This model is developed to function as the core of a reasoning mechanism of an intelligent support system that is able to create theory-based intervention messages. The system first tries to determine the reason of the occurrence of the unwanted behavior by asking short questions via a mobile phone application and by gathering information from an online lifestyle diary. The system then attempts to influence the user using tailored information and persuasive motivational messages.