All Outputs (8)

Using Semantic Technology to Model Persona for Adaptable Agents (2021)
Presentation / Conference Contribution
Nguyen, J., Farrenkopf, T., Guckert, M., Powers, S., & Urquhart, N. (2021, June). Using Semantic Technology to Model Persona for Adaptable Agents. Presented at ECMS 2021

In state of the art research a growing interest in the application of agent models for the simulation of road traffic can be observed. Software agents are particularly suitable for the representation of travellers and their goal-oriented behaviour. A... Read More about Using Semantic Technology to Model Persona for Adaptable Agents.

An overview of agent-based traffic simulators (2021)
Journal Article
Nguyen, J., Powers, S. T., Urquhart, N., Farrenkopf, T., & Guckert, M. (2021). An overview of agent-based traffic simulators. Transportation Research Interdisciplinary Perspectives, 12, Article 100486. https://doi.org/10.1016/j.trip.2021.100486

Individual traffic significantly contributes to climate change and environmental degradation. Therefore, innovation in sustainable mobility is gaining importance as it helps to reduce environmental pollution. However, effects of new ideas in mobility... Read More about An overview of agent-based traffic simulators.

Using AGADE Traffic to Analyse Purpose-driven Travel Behaviour (2021)
Presentation / Conference Contribution
Nguyen, J., Powers, S. T., Urquhart, N., Farrenkopf, T., & Guckert, M. (2021, October). Using AGADE Traffic to Analyse Purpose-driven Travel Behaviour. Presented at PAAMS: International Conference on Practical Applications of Agents and Multi-Agent System

AGADE Traffic is an agent-based traffic simulator that can be used to analyse purpose-driven travel behaviour of individuals that leads to the emergence of systemic patterns in mobility. The simulator uses semantic technology to model knowledge of in... Read More about Using AGADE Traffic to Analyse Purpose-driven Travel Behaviour.

Modelling Individual Preferences to Study and Predict Effects of Traffic Policies (2021)
Presentation / Conference Contribution
Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (2021, October). Modelling Individual Preferences to Study and Predict Effects of Traffic Policies. Presented at PAAMS: International Conference on Practical Applications of Agents and Mu

Traffic can be viewed as a complex adaptive system in which systemic patterns arise as emergent phenomena. Global behaviour is a result of behavioural patterns of a large set of individual travellers. However, available traffic simulation models lack... Read More about Modelling Individual Preferences to Study and Predict Effects of Traffic Policies.

Optimisation Algorithms for Parallel Machine Scheduling Problems with Setup Times (2021)
Presentation / Conference Contribution
Kittel, F., Enekel, J., Guckert, M., Holznigenkemper, J., & Urquhart, N. (2021, July). Optimisation Algorithms for Parallel Machine Scheduling Problems with Setup Times. Presented at Genetic and Evolutionary Computation Conference (GECCO '21), Online

Parallel machine scheduling is a problem of high practical relevance for the manufacturing industry. In this paper, we address a variant in which an unweighted combination of earliness, tardiness and setup times aggregated in a single objective funct... Read More about Optimisation Algorithms for Parallel Machine Scheduling Problems with Setup Times.

A Conceptual Framework for Establishing Trust in Real World Intelligent Systems (2021)
Journal Article
Guckert, M., Gumpfer, N., Hannig, J., Keller, T., & Urquhart, N. (2021). A Conceptual Framework for Establishing Trust in Real World Intelligent Systems. Cognitive Systems Research, 68, 143-155. https://doi.org/10.1016/j.cogsys.2021.04.001

Intelligent information systems that contain emergent elements often encounter trust problems because results do not get sufficiently explained and the procedure itself can not be fully retraced. This is caused by a control flow depending either on s... Read More about A Conceptual Framework for Establishing Trust in Real World Intelligent Systems.

Automated, Explainable Rule Extraction from MAP-Elites archives (2021)
Presentation / Conference Contribution
Urquhart, N., Höhl, S., & Hart, E. (2021, April). Automated, Explainable Rule Extraction from MAP-Elites archives. Presented at EvoAPPs2021, Online

Quality-diversity(QD) algorithms that return a large archive of elite solutions to a problem provide insights into how high-performing solutions are distributed throughout a feature-space defined by a user — they are often described as illuminating t... Read More about Automated, Explainable Rule Extraction from MAP-Elites archives.

Real Time Optimisation of Traffic Signals to Prioritise Public Transport (2021)
Presentation / Conference Contribution
Plötz, P., Wittpohl, M., & Urquhart, N. (2021, April). Real Time Optimisation of Traffic Signals to Prioritise Public Transport. Presented at EvoApplications 2021, Online

This paper examines the optimisation of traffic signals to prioritise public transportation (busses) in real time. A novel representation for the traffic signal prioritisation problem is introduced. Through the novel representation a creative evoluti... Read More about Real Time Optimisation of Traffic Signals to Prioritise Public Transport.