Integrated assessment models (IAMs) are a cornerstone of an effective approach to
climate change mitigation. Despite the variety of methodologies for characterising
the energy system, land use change, economics, and climate response, the modelling
community has an open and urgent request for tools capable of more realistic interpretation of the energy transition, capturing human behaviour, and embodying the
principles of transparency, reproducibility, and flexibility of use.
This paper presents an open-source modelling framework designed to fill that
gap. Named MUSE (ModUlar energy systems Simulation Environment), this new
agent-based model supports flexible characterisation of agent decision-making, including individual goals, bounded-rationality, imperfect foresight, and limited knowledge during the decision process. MUSE integrates this agent-based approach in a
partial-equilibrium framework and enables a technology-rich description of the energy systems with an unprecedented degree of flexibility for including technological,
temporal, and geographical granularity. The structure of MUSE creates the ability
to produce climate change mitigation assessments that are more grounded, and more
tangible model outputs for conceiving effective approaches to mitigation. MUSE is
available open source under a GNU General Public License v3.0 on GitHub at this
link https://github.com/SGIModel/MUSE_OS.