Uncovering leverage points involves understanding feedback loops that link variables, or factors, that cause behavior in other variables. Feedback loops are either self-reinforcing (good or bad) or goal-seeking (seeking equilibrium). Synthesis of improved courses of action arises from mitigating bad (vicious circles) self-reinforcing feedback loops, exploiting good (virtuous circles) and goal-seeking feedback loops, and iteratively optimizing them, typically using parameter-driven simulations. Leverage point models accomplish this simulation capability in software tools that follow system dynamics conventions. These conventions capture model structure and attach algebraic relationships to all the variables appearing in a diagram, including time span and steps.