‘Uncertainty reasoning” refers in a general way to problems discussed by that subset of the AI community interested in representing and reasoning with knowledge that cannot be expressed as certainties. The range of problems discussed runs the gamut from fundamental philosophical inquiry into the nature of uncertainty and how (if at all) it can be measured and modelled, to practical performance issues arising from the (automatic) construction of real-world models and making inferences from such models.

The last ten years have seen a marked increase of interest in agent-oriented technology, in several areas of computer science, including both software engineering and artificial intelligence. Agents are being used, and touted, for applications as diverse as personalised information management, electronic commerce, interface design, computer games, and management of complex commercial and industrial processes. Several deployed systems already use agent technology, and many more commercial and industrial applications are in development.

Cooperation is often presented as one of the key concepts which differentiates multi-agent systems from other related disciplines such as distributed computing, object-oriented systems, and expert systems. However, it is a concept whose precise usage in agent-based systems is at best unclear and at worst highly inconsistent. Given the centrality of the issue, and the different ideological viewpoints on the subject, this was a lively panel which dealt with the following main issues.

As computer scientists, our goals are motivated by the desire to improve computer systems in some way: making them easier to design and implement, more robust and less prone to error, easier to use, faster, cheaper, and so on. In the field of multi-agent systems, our goal is to build systems capable of flexible autonomous decision making, with societies of such systems cooperating with one-another. There is a lot of formal theory in the area but it is often not obvious what such theories should represent and what role the theory is intended to play. Theories of agents are often abstract and obtuse and not related to concrete computational models.

In spite of the rapid spread of agent technology, there is, as yet, little evidence of an engineering approach to the development of agent-based systems. In particular, development methods for these systems are relatively rare. One of the key reasons for this is the inadequacy of standard software development approaches for these new, and fundamentally different, agent-based systems. Traditional software development methods often lack the flexibility to handle high-level concepts such as an agent's dynamic control of its own behaviour, its ability to represent cooperative interactions, and its mechanisms for representing internal change, assumptions, objectives, and the uncertainty inherent in its interactions with the real-world.