Page 200 - Socially Intelligent Agents Creating Relationships with Computers and Robots

Socially Situated Planning 183

will be made clearer in the discussion below. These social control programs
can be viewed as defining a finite state machine that changes the state of the set
of control primitives based on features of the social context. In the examples
in this chapter this state machine is defined in terms of a set of condition action
rules, although in one application these state transitions have been formalized
in terms of STRIPS-style planning operators and the social-program actually
synthesized by the planning system [2].

2. Illustration
This approach has been used to model the behavior of military organizations
[2] but the following contrived example provides a clearer view of the capabil-
ities of the system. In this example, two synthetic characters, Jack and Steve,
interact in the service of their own conflicting goals. The interaction is deter-
mined dynamically as the agents interact with each other, but is also informed
by static information (e.g. the social stance they take towards one another).
These agents are embodied in a distributed virtual environment developed
by Rickel and Johnson [6] that provides a set of perceptual, communicative and
motor processes to control 3D avatars (see figure 22.1) that gesture and exhibit
facial expressions. The agents share task knowledge encoded as STRIPS-style
operators. They know how to drive vehicles to different locations, how to surf,
and how to buy lottery tickets. They also have individual differences. They
have differing goals, have varying social status and view their relationship with
each other differently.

Figure 22.1. The 3D avatars Jack and Steve.
Jack’s goal is to make money. Steve wants to surf. Both agents develop
different plans but have to contend with a shared resource (a car). Besides