By Vicente Botti, Adriana Giret (auth.)
ANEMONA is a multi-agent method (MAS) method for holonic production process (HMS) research and layout, in keeping with HMS requisites. ANEMONA defines a combined top-down and bottom-up improvement strategy, and gives HMS-specific instructions to assist the dressmaker in picking out and imposing holons. In ANEMONA, the desired HMS is split into concrete facets that shape various "views" of the system.
The improvement strategy of ANEMONA presents transparent and HMS-specific modeling instructions for HMS designers, and whole improvement stages for the HMS lifestyles cycle. The research section is outlined in phases: method requisites research, and Holon identity and Specification. This research offers high-level HMS necessities from the necessities, adopting a top-down recursive technique. a bonus of this recursive research is that its effects, i.e. the research versions, supply a collection of straightforward components and assembling ideas. the following level is Holon layout, a bottom-up strategy to supply the process structure from the research types of the former degree. The Holons Implementation level produces an Executable Code for the SetUp and Configuration degree. eventually, maintenances features are accomplished within the Operation and upkeep stage.
ANEMONA: A Multi-agent method for Holonic production Systems can be of curiosity to researchers and postgraduate scholars enthusiastic about synthetic intelligence and software program engineering, in addition to to production engineers in and academia.
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Extra info for ANEMONA: A Mulit-agent Methodology for Holonic Manufacturing Systems
Bussmann  proposes the use of multi-agent systems as the allowing technology for information processing in HMS. Starting with the holonic vision, multi-agent systems can provide the necessary reasoning techniques to develop the information processing architecture of a holon and the necessary cooperation techniques so that holons can interact with other holons forming holarchies. For the physical processing part, Fletcher and Deen  propose functional blocks to manage real-time control for low-level process/machine interaction.
Today, MAS is a very active area of research and is beginning to see commercial and industrial applications. MAS is centered on the social behavior of intelligent entities and focuses mainly on investigating behavior models, cooperation and coordination strategies, intelligent brokerage, task-performance optimization, learning from own experiences, coalition formation, etc. In summary, MAS is a general software technology motivated by fundamental research queries on subjects like autonomy, cooperation, group formation, etc.
Nevertheless, it is the only study that considers the global manufacturing system integrated in the company. 3 Multi-agent System Methods In this section we present a summary of the better-known MAS methodologies in the agent field. We classify them into two big clusters: general-purpose MAS methods1 and MAS methods for manufacturing systems. 1 General-purpose MAS Methods In this section we summarize some of the better-known MAS methodologies. 1 In this cluster of general-purpose methodologies we can find different clusters, for example, role-based methods, agent-based methods, organization-based methods, system-based methods, interaction-based methods, behavior-based methods, extensions of knowledge-based methodologies, etc.