Default reasoning is concerned with making inferences in cases where the information at hand is incomplete. In such cases it is necessary to make plausible assumptions, which in default reasoning are based on default rules. This paper gives an introduction to the field. It discusses in depth one particular approach, default logic, including properties, semantics and computational models. It also gives an overview of other ideas and approaches.

Traditional approaches to plan representation have focused on the generation of a sequence of actions and orderings. Knowledge rich models, which incorporate plan rationale, provide benefits to the planning process in a number of ways. The use of rationale in planning is reviewed in terms of causality, dependencies, and decisions. Each dimension addresses practical issues in the planning process, and adds value to the resultant plan. The contribution of this paper is to explore this categorisation, and to motivate the need to explicitly record and represent rationale knowledge for situated, mixed-initiative planning systems.

Information retrieval is the science concerned with the efficient and effective storage of information for the later retrieval and use by interested parties. During the last forty years, a plethora of information retrieval models and their variations have emerged. Logic-based models were launched to provide a rich and uniform representation of information and its semantics with the aim to improve information retrieval effectiveness. This approach was first advanced in 1986 by Van Rijsbergen with the so-called logical uncertainty principle. Since then, various logic-based models have been developed. This paper presents an introduction to and a survey of the use of logic for information retrieval modelling.

Interest in agent-oriented technology continues to grow, both at a theoretical level and a practical level, with the UK maintaining a strong representation in the area in both academic institutions and commercial organizations. In December 1997, the Second UK Workshop on Foundations of Multi-Agent Systems (FoMAS'97), held at the University of Warwick, built on the success of FoMAS'96 a year earlier (Luck, 1997; Doran et al., 1997; d'Inverno et al., 1997; Fisher et al., 1997) in seeking to provide a forum for academics and industrialists within the UK to present and discuss current directions in research and applications development. Supported by the EPSRC and HP Labs, FoMAS'97 was expanded to two days with invited presentations from Professor Ken Binmore of UCL, and Professor Cristiano Castelfranchi of the Italian National Research Council's Institute of Psychology, in addition to paper presentations and panel discussions. The aim again was to provide an opportunity for promoting and supporting activity in the research and development of multi-agent systems.

As the number of deployed multi-agent applications increases, further and better experience with the technology is gained, enabling a strong evaluation of the field from a more practical perspective. In particular, questions relating to how the theory of multi-agent systems impacts on practice, and how the practical development itself compares with other technologies, can be answered in the light of a heightened level of maturity. Given the tensions between theoreticians and practitioners in computing in general, let alone their spats in AI or multi-agent systems in particular, the discussion on agent systems and applications was both vigorous and enthusiastic

This report is the result of a panel discussion at the Second UK Workshop on Foundations of Multi-Agent Systems (FOMAS'97). All members of the panel are authors, listed alphabetically.