A deterministic model makes each action in a given state produce a uniquely determined outcome. In deterministic search, the same starting point follows the same procedural path each time. section 2.2 section 12.1.1
Determinism matters when choosing a search or planning method:
- Deterministic methods include graph search such as depth-first search, breadth-first search, Dijkstra, and A*, as well as gradient-based methods. section 2.2
- When the environment is uncertain, a deterministic model may not capture possible outcomes; stochastic planning instead uses transition probabilities. section 1.4.3 section 12.1.1
Planning a commute
A deterministic route plan estimates fixed travel times for train, car, or bike. If missed trains or varying traffic can change the outcome, a stochastic model represents those possibilities with probabilities. section 12.1.1
Figure 2.16 Deterministic vs. stochastic algorithms. Deterministic algorithms follow a set procedure, and the results are repeatable, while stochastic searches have elements of randomness built into the algorithms.
Compare repeatable procedures with searches that incorporate randomness. section 2.2
