Page 34 - Socially Intelligent Agents Creating Relationships with Computers and Robots

Creating Relationships with Computers and Robots 17

In chapter 30, Peyman Faratin considers the relationship between knowl-
edge, computation and the quality of solution for an agent involved in ne-
gotiation. Starting from a fairly classical game-theory model he relaxes the
assumptions in order to approach the situation real computational agents will
find themselves in. His results indicate that the type of cognitive model that the
agents have in a negotiation substantially effects the outcome and he concludes
that learning is an important skill for an agent involve in a realistic negotiation.
Scott Moss (chapter 31) uses agent-based simulations to try to understand
social systems. This paper is an interim report on an attempt to understand
negotiation between humans by investigating negotiation between agents. He
grounds his model with a real example of negotiation: the multi-party negoti-
ation between the various parties interested in the Meuse river. In this model
agents negotiation over a multi-dimensional space of possibilities where each
agent will not only have different goals but also attach different importance to
different goals. His agents learn who to negotiate with based upon observa-
tions of the other agents with respect to properties such as: trustworthiness,
reliability and similarity. His result is that although two agents succeed three
or more fail. This indicates that coalitions of agents might be critical to the
success of any multi-party negotiation (as well as the difficulty of the task).
In chapter 32 Juan A. Rodríguez-Aguilar and Carles Sierra start from a
macro perspective to try and design "organization centered" MAS. Like Scott
Moss they do not start from traditional a priori models, but take a real human
example (in this case a fish market) as their guide. From this they abstract what
they see as the principle institutional components and show how this can lead
to an effective open and agent-mediated institution. They claim that claim that
such a computational model is general enough to found the development of
other agent institutions.
The last chapter of the book (33) by Helen McBreen is an empirical study
of the reaction of people to virtual sales assistants. These assistants are 3D
embodied conversational agents that interact with a customer. She evaluated
customers’ reactions in three interactive VRML e-commerce environments: a
cinema box office, a travel agency and a bank. She found that the customers
carried over their expectations in terms of dress from the real world and that
they found it hard to trust the banking agent.

3. Common Themes
As mentioned above, many themes that are addressed in the 33 chapters
apply across different chapters. A few selected themes are listed in Figure 1.3.
This ‘mental map’ might help readers with specific interests in navigating the
book.