Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Table 1

Overview of requirements for energy transition management models.

	Agents are detailed, heterogeneous, and strategizing. They learn in interaction with each other and the environment. Behavior is defined through interviews and surveys. Exceptional individuals and institutions can drive innovation.		Global level with technological innovation through science, R&D, and economies of scale. Also, climate impacts and policies. Ability for rich nations to invest in climate mitigation in poorer nations (e.g., rainforests).
	Technology is detailed, disaggregated, decentralized, and validated by domain experts. Agent adoption drives endogenous, possibly exponential, bottom-up feedback loops for, for example, solar, wind, storage, and EVs.		National level with energy related policy, subsidy, and taxes. Also, large scale energy production/use, high voltage grids, and mobility patterns. Important level for modelling regime resistance.
	Ability to price externalities differently for different actors. Underlying assumptions are explicit and user adjustable, for example, discount rates, Negishi welfare weights, chance of catastrophe, and value of health/ecosystems.		Local level with actors that drive adoption and use of new energy technology. Constrained by spatially modelled physical infrastructure, connecting subsystems like grids, roads, buildings, machines, and people.