

![0_image_0.png](0_image_0.png)

probability :2) only when the robot ends up in the oce, then this correlation is duplicated to model schematically the conditional state-transition distributions given any particular diagrams (see Section 4.3), we call these nodes decision nodes and depict them in our net2TBN with an explicit decision node is shown in Figure 22. In this restricted example, we might imagine the decision node can take one of two values, Clk or CClk The fact that

Figure 21: An explicit-event model that removes correlations.

eects) are duplicated across actions as well. For instance, if coee request occurs (with

across all actions. more compelling example might be one in which the robot can move

briefcase to new location in one of number of ways. We'd like to capture the fact (or

ramication) that the contents of the briefcase move to the same location as the briefcase

regardless of the action that moves the briefcase.

To circumvent this diculty, we can introduce the choice of action as \random variable" in the network, conditioning the distribution over state variable transitions on the

value of this variable. Unlike state variables (or event variables in explicit event models),

we do not generally require distribution over this action variable|the intent is simply

choice of action. This is because the choice of action will be dictated by the decision maker

once policy is determined. For this reason, anticipating terminology used for in
uence

work diagrams with boxes. Such variable can take as its value any action available to the

agent.

the issuance of coee request at t+1 depends on whether the robot successfully moved from

rather than repeated across multiple action networks. Furthermore, the noisy persistence

undercuts this advantage as we will see when we try to combine actions).

One diculty with this straightforward use of decision nodes (which is the standard

representation in the in
uence diagram literature) is that adding candidate actions can

cause an explosion in the network's dependency structure. For example, consider the two

(or remained in) the oce is now represented \once" by the arc between Loct+1 and CRt+1

of under both actions is also represented only once (adding the action PUM however,

$$L o c^{t+1}$$
$$P\,U M$$