Frameworks for Reasoning about Agent Based Systems
نویسندگان
چکیده
This paper suggests formal frameworks that can be used as the basis for defining, reasoning about, and verifying properties of agent systems. The language, Little-JIL is graphical, yet has precise mathematically defined semantics. It incorporates a wide range of semantics needed to define the subtleties of agent system behaviors. We demonstrate that the semantics of Little-JIL are sufficiently well defined to support the application of static dataflow analysis, enabling the verification of critical properties of the agent systems. This approach is inherently a top-down approach that complements bottom-up approaches to reasoning about system behavior.
منابع مشابه
Improving Agent Performance for Multi-Resource Negotiation Using Learning Automata and Case-Based Reasoning
In electronic commerce markets, agents often should acquire multiple resources to fulfil a high-level task. In order to attain such resources they need to compete with each other. In multi-agent environments, in which competition is involved, negotiation would be an interaction between agents in order to reach an agreement on resource allocation and to be coordinated with each other. In recent ...
متن کاملUrban Vegetation Recognition Based on the Decision Level Fusion of Hyperspectral and Lidar Data
Introduction: Information about vegetation cover and their health has always been interesting to ecologists due to its importance in terms of habitat, energy production and other important characteristics of plants on the earth planet. Nowadays, developments in remote sensing technologies caused more remotely sensed data accessible to researchers. The combination of these data improves the obje...
متن کاملBalancing Formal and Practical Concerns in Agent Design
Most agent frameworks can be readily characterized into one of two groups. On the one hand, there are frameworks designed to have well-defined formal semantics, enabling formal reasoning about agents and their behavior. On the other hand, there are frameworks targeted at developing agent systems that can be deployed as practical applications interacting in highly dynamic real-world environments...
متن کاملLoad-Frequency Control: a GA based Bayesian Networks Multi-agent System
Bayesian Networks (BN) provides a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of load-frequency control (LFC). In practice, LFC systems use proportional-integral controllers. However since these controllers are designed using a linear model, the nonlinearities...
متن کاملApplying Proto-Frameworks in the Development of Multi-Agent Systems
Current trends in software development are increasingly reasoning about software applications in terms of multi-agent systems (MAS). However, the development of multi-agent applications is still a technically difficult task. One of the main barriers is the lack of comprehensive design practices to move systematically from problem analysis and agent models to effective implementations. This work...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2000