FSMs, Behavior Trees and HTNs produce degrees of adaptive decision-making and planning without any explicit quantification of priority of individual behviors. While Behavior Trees can implicitly allow for emulating priority by ordering of its higher priority behaviors to run before other lower ones (and using active-selectors), this however is static predefined order that does not varying to simulate changing priorities.
Utility systems however allow for candidate actions to be valued, measured and compared by giving them relative action-values (utility scores) that represents a notion of priority or action-desirability. Crucially, these values can vary over time depending on circumstance, and therefore can model adaptive prioritisation of situational behavior.
The general concept is that all possible actions are evaluated and the top scoring action is selected. This methodology is however most often used in evaluating the utility of goals, which then drive the execution of plans in Behavior Trees, GOAP and HTNs to run behaviors/actions to solve those goals.
A key aspect of utility systems is that single utility values can be composed of multiple independant decision factors that contribute to the overall utility that are derived from situational characteristics and context. Typically these are normalized values between and including 0 and 1 with high utility/desirability tending towards 1.
This means a utility score can then be composed of multiple influencing factors (decision factors) that augment the overall utility and therefore influence selection of the goal/behavior. These factors can themselves also be weighted to dampen or improve their influence in the overall utility score:
\[ Utility = w_1 \cdot Safety + w_2 \cdot Efficiency + w_3 \cdot Comfort \tag{Weighted decision factors} \]
Combining dynamic selection of goals based on evolving priorities using utility ststems, and coupled with structured but adaptive planning constructs in Behavior Trees and HTNs provides the blueprint for the flexible, adaptive and semi-autonomous behavior found in most games.