An adaptive multi-agent organization model based on dynamic role allocation

Multi Agent Based Dynamic Task Allocation

Multi-Agent system, which is relatively a recent term, can be viewed as a sub-field of Distributed AI. In order to construct and solve complex real world problems like task allocation in an organization, a number of agents can perform work cooperatively and collaboratively. To achieve the maximum system utility through the proper task allocation among agents, there is a notion of dynamic team f...

Dynamic Ontology Co-construction based on Adaptive Multi-Agent Technology

mortality forecasting based on lee-carter model

over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...

Multi-Agent Distributed Adaptive Resource Allocation (MADARA)

The component placement problem involves mapping a component to a particular location and maximizing component utility in grid and cloud systems. It is also an NP hard resource allocation and deployment problem, so many common grid and cloud computing libraries, such as MPICH and Hadoop, do not address this problem, even though large performance gains can occur by optimizing communications betw...

A Dynamic Network Simulation Model Based on Multi-Agent Systems

This paper reports on how the abstraction approach of multi-agent systems can be used to represent the complexity inherent in the urban traffic domain, accounting for the importance of modelling travellers’ behaviour and their interaction with intelligent transportation technologies. A key premise in the approach proposed is the identification of what we have coined autonomous decision entities...