×B2. Advances in agent-based modelling in biological, ecological and agricultural systems

Agent-Based Modelling (ABM) has long been applied to the study of complex phenomena. Over the past decade, it has become increasingly popular across many scientific fields including the study of biological, ecological and agricultural systems. Agent-Based models provide a rich environment for the experimentation and analysis of these systems at different levels of complexity by conceptually breaking them down into individual interacting components. The study of emergent trends that result from complex interactions can yield valuable insight into a range of systems.

This session provides a forum for the dissemination of advances in applying ABM approaches to the development of simulation systems in biology, ecology and agriculture. Submissions addressing the scientific challenges of modelling these systems using the ABM paradigm and novel approaches for dealing with statistical inference of these models are welcomed. Areas of interest, not necessarily exhaustive, include geo-spatial ABMs, hybrid models, model validation and verification, applications of parallel/distributed computing, integration with commercial off-the-shelf or open source Geographical Information Systems, optimisation techniques, ABM-enhanced Decision Support Systems, mobile applications, likelihood-free techniques for ABMs such as Approximate Bayesian Computation, Bayesian indirect inference and Bayesian synthetic likelihood.

Key topics: Agent based modelling, Complex systems, Emergent behaviour, Simulation systems