Abstract: This paper studies the use of agent communication in ubiquitous computing. This application domain allows us to investigate the efficient handling of large quantities of information in agent-based systems. We will present an approach to dynamically set up a communication network between agents which aims to minimize the communication load. The approach is based on a formal ontological notion of informativeness, on quantitative measures such as information gain and on the proper use of interaction mechanisms such as Publish/Subscribe. We also present experimental results which have been obtained using our prototyping tool called Ubismart.
Abstract: An experimental automated dialogue system that plays the role of a crisis hotline dispatcher is currently developed. Besides controlling the communication flow, this system is able to retrieve information about crisis situations from user's input. It offers a natural user interaction by the ability to perceive and respond to human emotions. The system has an emotion recognizer that is able to recognize the emotional loading from user's linguistic content. The recognizer uses a database that contains selected keywords on a 2D "arousal" and "valence" scale. The output of the system provides not only the information about the user's emotional state but also an indication of the urgency of his/her information regarding to crisis. The dialogue system is able to start a user friendly dialogue, taking care of the content, context and emotional loading of user's utterances.
Abstract: Choice of an incorrect representation for the design of automation can dramatically increase
system complexity. Principles from Cognitive Systems Engineering (CSE), which can be used to
identify good representations about the way the ‘world works’, provide a good starting point
for automation design.
This paper discusses, that by choosing the right model for automation design the added
complexity can be limited. But what is the right model for automation? The model of the
environment, or ecology, is preferred above the mental models that human operators have
developed through interacting with the system. The technology has altered the work
environment of the human operator and can have implied to complex or too simplified mental
models. A too complex mental model will bring a too high cognitive load and a simplified
mental model will not be sufficient in all situations. Using the ecology as the basis for the
model of automation, the complexity of the automation is constrained to that of the actual
environment with a minimum share of automation induced complexity.
To illustrate this we considered the design of a conventional autopilot and one based on total
energy control and discuss the mental model pilots have for energy control. Energy control is
the fundamental physics of flight. It is part of the environment thus ecology for pilots and a
proper understanding of energy control helps the pilot to deal with unanticipated event as the
mountain wave condition.