AA is critical to the success of the E-Elves since, despite the range of sensing devices, Friday has considerable uncertainty about the user's intentions and even location; hence, Friday will not always have the appropriate information to make correct decisions. On the other hand, while the user has the required information, Friday cannot continually ask the user for input, since such interruptions are disruptive and time-consuming. There are four decisions in the E-Elves to which AA reasoning is applied: (i) whether a user will attend a meeting on time; (ii) whether to close an auction for a role; (iii) whether the user is willing to perform an open team role; and (iv) if and what to order for lunch. In this paper, we focus on the AA reasoning for two of those decisions: whether a user will attend a meeting on time and whether to close an auction for a role. The decision as to whether a user will attend a meeting on time is the most often used and most difficult of the decisions Friday faces. We briefly describe the decision to close an auction and later show how an insight provided by the model of strategies led to a significant reduction in the amount of code required to implement the AA reasoning for that decision. The decision to volunteer a user for a meeting is similar to the earlier decisions, and omitted for brevity; the decision to order lunch is currently implemented in a simpler fashion and is not (at least as yet) illustrative of the full set of complexities.

A central decision for Friday, which we describe in terms of our problem formulation,
{A, a, p, x, d, E}, is whether its user will attend a meeting at the currently scheduled meeting time. In this case, Friday is the agent, A. The joint activity, α, is for the meeting attendees to attend the meeting simultaneously. Friday acts as proxy for its user, hence its role, p, is to ensure that its user arrives at the currently scheduled meeting time. The coordination constraint, ~, between Friday's role and the roles of other Fridays is that they occur simultaneously, i.e., the users must attend at the currently scheduled time. If any attendee arrives late, or not at all, the time of all the attendees is wasted; on the other hand, delaying a meeting is disruptive to users' schedules. The decision, d, is whether the user will attend the meeting or not and could be made by either Friday or the user, i.e., E = {user, Friday}. Clearly, the user will be often better placed to make this decision.

However, if Friday transfers control to the user for the decision, it must guard against miscoordination, i.e., having the other attendees wait, while waiting for a user response. Some decisions are potentially costly, e.g., incorrectly telling the other attendees that the user will not attend, and Friday should avoid taking them autonomously. To buy more time for the user to make the decision or for itself to gather more information, Friday could change coordination constraints with a D action. Friday has several different D actions at its disposal, including delaying the meeting by different lengths of time, as well as being able to cancel the meeting entirely. The user can also request a D action, e.g., via the dialog box in Figure 5(a), to buy more time to make it to the meeting. If the user decides a D is required, Friday is the conduit through which other Fridays (and hence their users) are informed.

Friday must select a sequence of actions, either transferring control to the user, delaying or cancelling the meeting or autonomously announcing that the user will or will not attend, to maximize the utility of the team.

The second AA decision that we look at is the decision to close an auction for an open role and assign a user to that role. 2 In this case, the joint activity, α , is the group research