Selecting a multi-agent system development tool for industrial applications: A case study of self-serving aircraft assets

Industrialists have few example processes they can benchmark against in order to choose a multi-agent development kit. In this paper we present a review of commercial and academic agent tools with the aim of selecting one for developing an intelligent, self-serving asset architecture. In doing so, we map and enhance relevant assessment criteria found in literature. After a preliminary review of 20 multiagent platforms, we examine in further detail those of JADE, JACK and Cougaar. Our findings indicate that Cougaar is well suited for our requirements, showing excellent support for criteria such as scalability, persistence, mobility and lightweightness. © 2010 IEEE.

New robotics: design principles for intelligent systems.

New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e. g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only "nice to have" but is in fact a necessary tool for designing embodied agents.

The design of an agent for modelling supply chain network dynamics

A useful insight into managerial decision making can be found from simulation of business systems, but existing work on simulation of supply chain behaviour has largely considered non-competitive chains. Where competitive agents have been examined, they have generally had a simple structure and been used for fundamental examination of stability and equilibria rather than providing practical guidance to managers. In this paper, a new agent for the study of competitive supply chain network dynamics is proposed. The novel features of the agent include the ability to select between competing vendors, distribute orders preferentially among many customers, manage production and inventory, and determine price based on competitive behaviour. The structure of the agent is related to existing business models and sufficient details are provided to allow implementation. The agent is tested to demonstrate that it recreates the main results of the existing modelling and management literature on supply chain dynamics. A brief exploration of competitive dynamics is given to confirm that the proposed agent can respond to competition. The results demonstrate that overall profitability for a supply chain network is maximised when businesses operate collectively. It is possible for an individual business to achieve higher profits by adopting a more competitive stance, but the consequence of this is that the overall profitability of the network is reduced. The agent will be of use for a broad range of studies on the long-run effect of management decisions on their network of suppliers and customers.