Page 33 - Socially Intelligent Agents Creating Relationships with Computers and Robots

16 Socially Intelligent Agents

In chapter 27, Michael Mateas and Andrew Stern describe their approach to
building an interactive drama system in which a human user participates in a
dramatic story and thereby experiences it from a first person perspective. The
main problem is to design agents with less than human abilities but which can
nevertheless play believable roles in a range of situations. Their approach is to
provide a drama manager agent which keeps the overall action on course, and
also thereby reduces the demands on characters who therefore need only use
local plans applicable in the vicinity of the story line.
Michael Young discusses another approach to interactive drama in chapter
28. The narrative structure of the games is generated dynamically, and its main
principle is to manage a cooperative contract with the user. This consists of
dramatical expectations built upon social commitments. The system creates,
modifies and maintains a narrative plan using dramatical principles, and the
unfolding of action is designed to provide an interesting narrative experience
for the user.
In chapter 29 Nell Tenhaaf manages to bring together the treatments of self
for interactive agents produced by artists for interactive art and those produced
by computer scientists for intelligent agent applications. Her discussion illu-
minates the depth of this subject and points us to its sophisticated literature.
She also describes in detail one particular interactive work entitled ‘Talk Nice’
made by fellow artist Elizabeth Van Der Zaag. Using video and a speech recog-
nition system, this implements a bar ‘pick up’ social situation where the user
has to talk nice to succeed.

2.8 Social Agents in E-Commerce
It is not surprising to find a section of this book dealing with commerce,
since the exchange of value is one of the principle social mechanisms humans
use. In the last century economics tried to strip exchange of its social aspects
by the use of strong normative assumptions. Their models insisted (in practice)
of very limited and selfish goals for its agents, they limited communication to
the barest minimum (usually to price alone) and they almost totally ignored any
process preferring to concentrate on equilibrium states instead. Now that it is
becoming increasingly clear that this approach has failed, there is a renewed
interest in using MAS to model these processes – putting some of the critical
aspects that were jettisoned back in. At the same time the exchange of value
is being increasingly conducted using computational media. The effect of this
is to somewhat disembody the exchange process which makes it possible for
software agents to participate as near equals with humans. The confluence of
using societies of agents to model the complexities of social exchange and the
challenge of using them to perform that exchange reinforces the importance
social agents will have with respect to commerce in the next century.