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104 Socially Intelligent Agents

4 Tambe’s proxy automatically volunteered him for a presentation, though he was actually
unwilling. Again, C4.5 had over-generalized from a few examples and when a timeout
occurred had taken an undesirable autonomous action.
Fromthegrowinglistoffailures, itbecameclearthat theapproachfacedsome
fundamental problems. The first problem was the AA coordination challenge.
Learning from user input, when combined with timeouts, failed to address the
challenge, since the agent sometimes had to take autonomous actions although
it was ill-prepared to do so (examples 2 and 4). Second, the approach did not
consider the team cost of erroneous autonomous actions (examples 1 and 2).
Effective agent AA needs explicit reasoning and careful tradeoffs when dealing
with the different individual and team costs and uncertainties. Third, decision-
tree learning lacked the lookahead ability to plan actions that may work better
over the longer term. For instance, in example 3, each five-minute delay is
appropriate in isolation, but the rules did not consider the ramifications of one
action on successive actions. Planning could have resulted in a one-hour delay
instead of many five-minute delays. Planning and consideration of cost could
also lead to an agent taking the low-cost action of a short meeting delay while
it consults the user regarding the higher-cost cancel action (example 1).

4. MDPs for Adjustable Autonomy

Figure 12.2. A small portion of simplified
version of the delay MDP
Figure 12.1. Dialog for meetings

MDPs were a natural choice for addressing the issues identified in the previ-
ous section: reasoning about the costs of actions, handling uncertainty, planning
for future outcomes, and encoding domain knowledge. The delay MDP, typical
of MDPs in Friday, represents a class of MDPs covering all types of meetings
for which the agent may take rescheduling actions. For each meeting, an agent
can autonomously perform any of the 10 actions shown in the dialog of Fig-
ure 12.1. It can also wait, i.e., sit idly without doing anything, or can reduce its
autonomy and ask its user for input.