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Published online by Cambridge University Press: 19 May 2025
The motivations for acting and planning with probabilistic models are about handling uncertainty in a quantitative way, with optimal or near-optimal decisions. The future is never entirely and precisely predictable. Uncertainty can be due to exogenous events in the environment, from nature and other actors, to noisy sensing and information gathering actions, to possible failures and outcomes of imprecise or intrinsically nondeterministic actions. Models are necessarily incomplete. Knowledge about open environments is partial. Part of what may happen can be only be modeled with uncertainty. Even in closed predictable environments, complete deterministic models may be too complex to develop. The three chapters in Part III tackle acting, planning, and learning in a probabilistic setting.
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