EDI and intelligent agents integration to manage food chains

Electronic Data Interchange (EDI) is a type of inter-organizational information system, which permits the automatic and structured communication of data between organizations. Although EDI is used for internal communication, its main application is in facilitating closer collaboration between organizational entities, e.g. suppliers, credit institutions, and transportation carriers. This study illustrates how agent technology can be used to solve real food supply chain inefficiencies and optimise the logistics network. For instance, we explain how agribusiness companies can use agent technology in association with EDI to collect data from retailers, group them into meaningful categories, and then perform different functions. As a result, the distribution chain can be managed more efficiently. Intelligent agents also make available timely data to inventory management resulting in reducing stocks and tied capital. Intelligent agents are adoptive to changes so they are valuable in a dynamic environment where new products or partners have entered into the supply chain. This flexibility gives agent technology a relative advantage which, for pioneer companies, can be a competitive advantage. The study concludes with recommendations and directions for further research

OperA/ALIVE/OperettA

Comprehensive models for organizations must, on the one hand, be able to specify global goals and requirements but, on the other hand, cannot assume that particular actors will always act according to the needs and expectations of the system design. Concepts as organizational rules (Zambonelli 2002), norms and institutions (Dignum and Dignum 2001; Esteva et al. 2002), and social structures (Parunak and Odell 2002) arise from the idea that the effective engineering of organizations needs high-level, actor-independent concepts and abstractions that explicitly define the organization in which agents live (Zambonelli 2002).Peer ReviewedPostprint (author's final draft

Empathic Agent Technology (EAT)

A new view on empathic agents is introduced, named: Empathic Agent Technology (EAT). It incorporates a speech analysis, which provides an indication for the amount of tension present in people. It is founded on an indirect physiological measure for the amount of experienced stress, defined as the variability of the fundamental frequency of the human voice. A thorough review of literature is provided on which the EAT is founded. In addition, the complete processing line of this measure is introduced. Hence, the first generally applicable, completely automated technique is introduced that enables the development of truly empathic agents

Multi-agent systems for power engineering applications - part 2 : Technologies, standards and tools for building multi-agent systems

This is the second part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examined the potential value of MAS technology to the power industry, described fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications, and presented a comprehensive review of the power engineering applications for which MAS are being investigated. It also defined the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented. Given the significant and growing interest in this field, it is imperative that the power engineering community considers the standards, tools, supporting technologies and design methodologies available to those wishing to implement a MAS solution for a power engineering problem. The paper describes the various options available and makes recommendations on best practice. It also describes the problem of interoperability between different multi-agent systems and proposes how this may be tackled

Emotional persistence in online chatting communities

How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional "tone" of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication.Comment: 34 pages, 4 main and 12 supplementary figure

Multirelational Organization of Large-scale Social Networks in an Online World

The capacity to collect fingerprints of individuals in online media has revolutionized the way researchers explore human society. Social systems can be seen as a non-linear superposition of a multitude of complex social networks, where nodes represent individuals and links capture a variety of different social relations. Much emphasis has been put on the network topology of social interactions, however, the multi-dimensional nature of these interactions has largely been ignored in empirical studies, mostly because of lack of data. Here, for the first time, we analyze a complete, multi-relational, large social network of a society consisting of the 300,000 odd players of a massive multiplayer online game. We extract networks of six different types of one-to-one interactions between the players. Three of them carry a positive connotation (friendship, communication, trade), three a negative (enmity, armed aggression, punishment). We first analyze these types of networks as separate entities and find that negative interactions differ from positive interactions by their lower reciprocity, weaker clustering and fatter-tail degree distribution. We then proceed to explore how the inter-dependence of different network types determines the organization of the social system. In particular we study correlations and overlap between different types of links and demonstrate the tendency of individuals to play different roles in different networks. As a demonstration of the power of the approach we present the first empirical large-scale verification of the long-standing structural balance theory, by focusing on the specific multiplex network of friendship and enmity relations.Comment: 7 pages, 5 figures, accepted for publication in PNA