Developing effective and resilient human-agent teamwork using team design patterns

Human-agent teams exhibit emergent behavior at the team level, as a result of interactions between individuals within the team. This begs the question how to design artificial team members (agents) as adequate team players that contribute to the team processes advancing team performance, resilience and learning. This paper proposes the development of a library of Team Design Patterns as a way to make dynamic team behavior at the team and individual level more explicit. Team Design Patterns serve a dual purpose: (1) In the system development phase, designers can identify desirable team patterns for the creation of artificial team members. (2) During the operational phase, team design patterns can be used by artificial team members to drive and stimulate team development, and to adaptively mitigate problems that may arise. We describe a pattern language for specifying team design patterns, discuss their use, and illustrate the concept using representative human-agent teamwork applications

ABSTRACT Strategies for Ontology Negotiation: Finding the Right Level of Generality

In heterogeneous multi agent systems, communication is hampered by the lack of shared ontologies. Ontology negotiation is a technique that enables pairs of agents to overcome these difficulties by exchanging parts of their ontologies. As a result of these micro level solutions, a communication vocabulary emerges on a macro level. The goal of this paper is to ensure that this communication vocabulary contains words of the right level of generality, i.e. not overspecific and not overgeneralized. We will propose a number of communication strategies that enable the agents to achieve these goals. Using experimental results, we will compare their performance. 1

Supporting Human-Robot Teams in Space Missions using ePartners and Formal Abstraction Hierarchies

Human space flight is a prototypical example of a complex, dynamic, and safety-critical domain in which missions are performed by collaborative teams of humans and technical systems. In such domains, intelligent electronic partners (ePartners) can play a useful role in supporting human-robot teams in their problem solving process whenever a non-nominal situation is encountered. To enhance the supportive capabilities of such ePartners, this paper presents an approach to formally represent the functionality of human-robot teams in terms of different levels of abstraction. By establishing formal relations between domain knowledge at different abstraction levels and introducing reasoning rules to navigate through these relations, ePartners are endowed with a number of supportive functions, such as the ability to reason about the mission status, make suggestions in non-nominal situations, and provide explanations. The approach is applied to a use case in the context of a manned space mission to Mars. It has been implemented within a mobile application to assist robotastronaut teams during space missions, and has been tested in a pilot experiment at the European Space Research and Technology Centre

Agent Communication in Ubiquitous Computing: the Ubismart Approach

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