Outputs (56)

Multi-Agent Modelling Notation (MAMN): A multi-layered graphical modelling notation for agent-based simulations (2022)
Presentation / Conference Contribution
Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (2022, November). Multi-Agent Modelling Notation (MAMN): A multi-layered graphical modelling notation for agent-based simulations. Presented at 24th International Conference on Principles and Practice of Multi-Agent Systems, Valencia, Spain

Cause-effect graphs have been applied in non agent-based simulations, where they are used to model chained causal relations between input parameters and system behaviour measured by appropriate indicators. This can be useful for the analysis and inte... Read More about Multi-Agent Modelling Notation (MAMN): A multi-layered graphical modelling notation for agent-based simulations.

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.

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 Multi-Agent Systems, Salamanca, Spain

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.

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 Systems, Salamanca, Spain

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.

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.

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.

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.

Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation (2020)
Presentation / Conference Contribution
Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2020, February). Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation. Presented at Modelling 2020, Vienna

Multi-agent systems may be considered appropriate tools for simulating complex systems such as those based around traffic and transportation networks. Modelling traffic participants as agents can reveal relevant patterns of traffic flow. Upsurging tr... Read More about Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation.

An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem (2019)
Presentation / Conference Contribution
Urquhart, N., Hoehl, S., & Hart, E. (2019, July). An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem. Presented at Genetic and Evolutionary Computation Conference (GECCO '19), Prague, Czech Republic

An increasing emphasis on reducing pollution and congestion in city centres combined with an increase in online shopping is changing the ways in which logistics companies address vehicle routing problems (VRP). We introduce the {\em micro-depot}-VRP,... Read More about An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem.

Increasing Trust in Meta-Heuristics by Using MAP-Elites (2019)
Presentation / Conference Contribution
Urquhart, N., Guckert, M., & Powers, S. (2019, July). Increasing Trust in Meta-Heuristics by Using MAP-Elites. Presented at Genetic and Evolutionary Computation COnference, Prague, Czech Republic

Intelligent AI systems using approaches containing emergent elements often encounter acceptance problems. Results do not get sufficiently explained and the procedure itself can not be fully retraced because the flow of control is dependent on stochas... Read More about Increasing Trust in Meta-Heuristics by Using MAP-Elites.