Engineering Multiagent Systems - Reflections

This report documents the programme and outcomes of Dagstuhl Seminar 12342 ``Engineering multiagent Systems\u27\u27. The seminar brought together researchers from both academia and industry to identify the potential for and facilitate convergence towards standards for agent technology. As such it was particularly relevant to industrial research. A key objective of the seminar, moreover, has been to establish a road map for engineering multiagent systems. Various research areas have been identified as important topics for a research agenda with a focus on the development of multiagent systems. Among others, these include the integration of agent technology and legacy systems, component-based agent design, standards for tooling, establishing benchmarks for agent technology, and the development of frameworks for coordination and organisation of multiagent systems. This report presents a more detailed discussion of these and other research challenges that were identified. The unique atmosphere of Dagstuhl provided the perfect environment for leading researchers from a wide variety of backgrounds to discuss future directions in programming languages, tools and platforms for multiagent systems, and the road map produced by the seminar will have a timely and decisive impact on the future of this whole area of research

Belief revision, conditional logic, and nonmonotonic reasoning

Abstract We consider the connections between belief revision, conditional logic and nonmonotonic reasoning, using as a foundation the approach to theory change developed by Alchourrón, Gärdenfors and Makinson (the AGM approach). This is first generalized to allow the iteration of theory change operations to capture the dynamics of epistemic states according to a principle of minimal change of entrenchment. The iterative operations of expansion, contraction and revision are characterized both by a set of postulates and by Grove’s construction based on total pre-orders on the set of complete theories of the belief logic. We present a sound and complete conditional logic whose semantics is based on our iterative revision operation, but which avoids Gärdenfors’s triviality result because of a severely restricted language of beliefs and hence the weakened scope of our extended postulates. In the second part of the paper, we develop a computational approach to theory dynamics using Rott’s E-bases as a representation for epistemic states. Under this approach, a ranked E-base is interpreted as standing for the most conservative entrenchment compatible wit

AN INFORMATION-BASED THEORY OF CONDITIONALS

Abstract We present an approach to combining three areas of research which we claim are all based on information theory: knowledge representation in Artificial Intelligence and Cognitive Science using prototypes, plans, or schemata; formal semantics in natural language, especially the semantics of the ‘if-then’ conditional construct; and the logic of subjunctive conditionals first developed using a possible worlds semantics by Stalnaker and Lewis. The basic premise of the paper is that both schema-based inference and the semantics of conditionals are based on Dretske’s notion of information flow and Barwise and Perry’s notion of a constraint in situation semantics. That is, the connection between antecedent A and consequent B of a conditional ‘if A were the case then B would be the case ’ is an informational relation holding with respect to a pragmatically determined utterance situation. The bridge between AI and conditional logic is that a prototype or planning schema represents a situation type, and the background assumptions underlying the application of a schema in a situation correspond to channel conditions on the flow of information. Adapting the work of Stalnake

Agent-based modelling for risk assessment of routine clinical processes

Prospective risk analysis is difficult in complex sociotechnical systems where humans interact with one other and with information systems. Traditional prospective risk analysis methods typically capture one risk at a time and rely on the specification of a chronological sequence of errors occurring in combination. The aim here is to introduce agent-based risk assessment (ABRA), which addresses these issues by simulating multiple concurrent and sequential interactions amongst autonomous agents that act according to their own goals. The methodology underlying the construction, simulation and validation of ABRA models is detailed along with practical considerations associated with implementation, for which the Brahms agent-based simulation framework is used. The challenges of implementing agent-based risk assessment models include the need for well-defined work processes and reliable observational data, and difficulties associated with behavioural validation. As an example illustrating the technique, a simple race condition hazard is implemented using an ABRA model. The work process involves a human operator and a machine interface that interact to sometimes produce the erroneous transfer of information. The correctness of the model is confirmed by comparing the simulated results against the well-defined theoretical baseline.12 page(s