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

Proceedings of the 11th Workshop on Nonmonotonic Reasoning

These are the proceedings of the 11th Nonmonotonic Reasoning Workshop. The aim of this series is to bring together active researchers in the broad area of nonmonotonic reasoning, including belief revision, reasoning about actions, planning, logic programming, argumentation, causality, probabilistic and possibilistic approaches to KR, and other related topics. As part of the program of the 11th workshop, we have assessed the status of the field and discussed issues such as: Significant recent achievements in the theory and automation of NMR; Critical short and long term goals for NMR; Emerging new research directions in NMR; Practical applications of NMR; Significance of NMR to knowledge representation and AI in general

Heterogeneous temporal probabilistic agents

To date, there has been no work on temporal probabilistic agent reasoning on top of heterogeneous legacy databases and software modules. We will define the con-cept of a heterogeneous temporal probabilistic (HTP) agent. Such agents can be built on top of existing databases, data structures, and software code bases without explicitly accessing the internal code of those systems and can take actions compat-ible with a policy or operating principles specified by an agent developer. We will develop a formal semantics for such agents through the notion of a feasible tem-poral probabilistic status interpretation (FTPSI for short). Intuitively, an FTPSI specifies what all an HTP agent is permitted/forbidden/obliged to do at various times t. As changes occur in the environment, the HTP agent must compute a new FTPSI. HTP agents continuously compute FTPSI’s in order to determine what they should do and hence, the problem of computing FTPSI’s is very important. We give a sound and complete algorithm to compute FTPSI’s for a very large class of HTP agents called strict HTP agents. In a given state, many FTPSI’s may exist. These represent alternative courses of action that the HTP agent can take. We pro-vide a notion of an optimal FTPSI that selects an FTPSI optimising an objective function and give a sound and complete algorithm to compute an optimal FTPSI.

A Scalable Runtime Platform for Multiagent-Based Simulation

Abstract. Using purely agent-based platforms for any kind of simulation requires to address the following challenges: (1) scalability (efficient scheduling of agent cycles is difficult), (2) efficient memory management (when and which data should be fetched, cached, or written to/from disk), and (3) modelling (no generally accepted meta-models exist: what are essential concepts, what just implementation details?). While dedicated professional simulation tools usually provide rich domain libraries and advanced visualisation techniques, and support the simulation of large scenarios, they do not allow for "agentization" of single components. We are trying to bridge this gap by developing a distributed, scalable runtime platform for multiagent simulation, MASeRaTi, addressing the three problems mentioned above. It allows to plug-in both dedicated simulation tools (for the macro view ) as well as the agentization of certain components of the system (to allow a micro view ). If no agent-related features are used, its performance should be as close as possible to the legacy system used