Agent-based modelling has a long history of success in many related fields from economics and cooperative behaviours, to social conflict, civil violence and revolution.
This session aims to bring together researchers who are interested in using agent-based modelling to understand human behaviour. It is a combination of computational modelling, social science and behavioural science, which is a growing area of research. Our motivation is to improve our understanding of collective human behaviour and address significant issues that are affecting the human population today, such as climate change, the global pandemic and misinformation. Alife models offer the capability to create realistic laboratories for which to conduct experiments and progress our understanding in the area. We encourage researchers to use behavioural modelling to assess, challenge or even replace competing theories of human behaviour. Discussions of practical applications, ethical implications, and use cases from industry are also welcome. ABMHuB has been organised as a workshop in the past four ALife conferences: ABMHuB 2022, ABMHuB 2021, ABMHuB 2020 and ABMHuB 2019.
Contributions will be invited in the following areas:
- Agent-based modelling of human behaviour and organisational behaviour
- ALife models of individual behaviour, diversity, and group performance
- ALife models of human communication, trust, conflict, and conflict resolution
- ALife models of collaboration, cooperation, competition
- ALife models of social media and spread of misinformation
- Collective intelligence, teamwork, coalition, distributed problem solving
- Social networks, socio-technical systems
- Epidemiology and spread of diseases
- Social simulation, interactive simulation and emergent behaviour
- Education technology, personalised teaching and training.
- Incentives, reward structures, reinforcement learning
- Agent-based modelling of economic paradigms such as negotiation and bargaining, games, auctions, markets
- Agent-based modelling of location behaviour, spatial patterns, geographical systems, urban evacuation, driver route choices, traffic flows, transport logistics
- Agent-based modelling of human systems such as smart grids, app stores, economies
- ALife models of the emergent effect and propagation of communication in human systems
- Use of agent-based modelling to evaluate or understand existing findings in behavioural science and psychology