12.1 General Methods

This section presents planning methods for the problems introduced in Section 11.1. They are based mainly on general-purpose dynamic programming, without exploiting any particular structure to the problem. Therefore, their application is limited to small state spaces; nevertheless, they are worth covering because of their extreme generality. The basic idea is to use either the nondeterministic or probabilistic I-map to express the problem entirely in terms of the derived I-space, or , respectively. Once the derived information transition equation (recall Section 11.2.1) is defined, it can be imagined that or is a state space in which perfect state measurements are obtained during execution (because the I-state is always known).

- 12.1.1 The Information Space as a Big State Space
- 12.1.2 Algorithms for Nondeterministic I-Spaces

- 12.1.3 Algorithms for Probabilistic I-Spaces (POMDPs)

Steven M LaValle 2020-08-14