Stochastic dynamic programming is a single-objective optimisation approach which employs algorithms designed to optimise an objective function under specified constraints. Optimisation approaches can be viewed as providing the analytical machinery to assist in the generation and analysis of ‘target-seeking’ or ‘backcasting’ scenarios. With a detailed understanding of cause-and-effect, stochastic dynamic programming can accommodate non-linear, dynamic outcomes associated with stochastic risk (e.g. risks associated with wildfires) superimposed on the deterministic influence of management actions (e.g. fuel reduction burning in high fire risk places). SDP recognises that what might be considered a desirable action depends on the state of the system.