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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.compind.2009.02.007 Byline: Adriana Giret, Vicente Botti Keywords: Multi-agent Systems; Holonic Manufacturing Systems; Software engineering method Abstract: Holonic Manufacturing Systems (HMS) was first proposed as a new manufacturing paradigm at the beginning of 1990 and has subsequently received a lot of attention in academic and industrial research. The application of holonic concepts to manufacturing was initially motivated by the inadequacy of existing manufacturing systems in the following two aspects: (i) dealing with the evolution of products within an existing production facility, and (ii) maintaining a satisfactory performance outside of normal operating conditions. In spite of the large number of developments reported in Holonic Control Architectures and Holonic Control Algorithms, there is very little work reported on Methodologies for HMS. Manufacturing requirements impose significant properties on HMS making the modelling process of HMS a complex and difficult task. In this work we describe how to engineer Holonic Manufacturing Systems using a Multi-agent System method. Our approach is based on holonic systems specific requirements, and it incorporates software engineering principles in order to assist the system designers at each development stage. It implements a collaborative-engineering process for HMS, and provides clear and unambiguous analysis and design guidelines. Author Affiliation: Universidad Politecnica de Valencia, Departamento de Sistemas Informaticos y Computacion, Camino de Vera s/n-46022, Valencia, Spain

The database of prospective zeolites (www.hypotheticalzeolites.net) has been screened in search of feasible zeolites. Previous criteria of zeolite feasibility have been reviewed, based on descriptors such as energy, density, average and distribution of ring sizes, and more importantly that of Li et al. (LID criteria) presented recently [Angew. Chem. Int. Ed. 2013, 52, 1673], based on Si–O, O⋯O, and Si⋯Si distances of SLC-minimised structures. In spite of the still large number of feasible zeolites according to this and other criteria, a number of researchers wonder why there are so many feasible and so few synthesised zeolites. Without answering this difficult question, a new criteria is proposed in this study based on the fact that T⋯T⋯T angles (T is tetrahedral atom) show specific ranges of values depending on the ring size to which they belong. Based on improved definitions to count and enumerate rings in zeolites, and with data from the IZA database, we introduce the TTT criteria, which we propose to use after the LID criteria, to further narrow the space of feasible zeolites.

Nowadays, cloud computing is revolutionizing the services provided through the Internet to adapt itself in order to keep the quality of its services. Recent research foresees the advent of a new discipline of agent-based cloud computing systems that can make decisions about adaption in an uncertain environment. This paper discusses the role of argumentation in the next generation of agreement technologies and its use in cloud computing environments.Nowadays, cloud computing is revolutionizing the services provided through the Internet to adapt itself in order to keep the quality of its services. Recent research foresees the advent of a new discipline of agent-based cloud computing systems that can make decisions about adaption in an uncertain environment. This paper discusses the role of argumentation in the next generation of agreement technologies and its use in cloud computing environments.

The application of argumentation theories and techniques in multi-agent systems has become a prolific area of research. Argumentation allows agents to harmonise two types of disagreement situations: internal, when the acquisition of new information (e.g., about the environment or about other agents) produces incoherences in the agents' mental state; and external, when agents that have different positions about a topic engage in a discussion. The focus of this paper is on the latter type of disagreement situations. In those settings, agents must be able to generate, select and send arguments to other agents that will evaluate them in their turn. An efficient way for agents to manage these argumentation abilities is by using case-based reasoning, which has been successfully applied to argumentation from its earliest beginnings. This reasoning methodology also allows agents to learn from their experiences and therefore, to improve their argumentation skills. This paper analyses the advantages of applying case-based reasoning to manage arguments in multi-agent systems dialogues, identifies open issues and proposes new ideas to tackle them.

A soft computing technique based on the combination of Artificial Neural Networks (ANNs) and a Genetic Algorithm (GA) has been developed for the discovery and optimization of new materials when exploring a high-dimensional space. This technique allows the experimental design in the search of new solid materials with high catalytic performance when exploring simultaneously a large number of variables such as elemental composition, manufacture procedure variables, etc. This novel integrated architecture allows one to strongly increase the convergence performance when compared with the performance of conventional GAs. It is described how both artificial intelligence techniques are built to work together. Moreover, the influence of algorithm configuration and the different algorithm parameters in the final optimization performance have been evaluated. The proposed optimization architecture has been validated using two hypothetical functions, based on the modeled behavior of multi-component catalysts explored in the field of combinatorial catalysis.

The future of the manufacturing sector in the world will be determined by how it meets the challenges of the 21st century. Two paradigms promise to meet these challenges, multi-agent systems (MAS) and holonic system (HS). Currently, there is some misunderstanding about the relationships between these two approaches. The aim of this work is to make a study of all the characteristics of the HS and the MAS approach, in order to illustrate a comprehensive comparison of holons and agents, and, at the same time, to present a survey about the main research works in both areas.

This paper presents a framework appropriate for Flexible Real-Time Systems (FRTS) and a run-time support system based on that framework, called Flexible Real-Time Linux (FRTL). The framework proposes to build each task as a sequence of mandatory and optional components and to separate their execution in two scheduling levels. This approach is shown to provide both hard guarantees and flexible behavior. The FRTL system has been implemented by enhancing the original capabilities of Real-Time Linux (RT-Linux), while maintaining its predictability and efficiency features. This paper also shows a complete schedulability test on which all sources of overhead of the FRTL itself have been introduced. By applying this complete test, the designer is able to safely guarantee a real-time application running on the FRTL system.

Temporal representation and reasoning, as the ability of reasoning about temporal data, representing past, current and expected application states, is an important function to be accomplished by Real-Time Knowledge-Based Systems (RTKBS), since these systems are usually applied in dynamic time-dependent problem domains. However, this feature is not completely nor usually addressed in current RTKBS tools. In this paper, a RTKBS architecture is presented, with special emphasis on its temporal reasoning function, which is integrated in a RTKBS environment with a multi-agent blackboard architecture. Representation and management of temporal data, representing past, current and future problem states and reasoning processes within these contexts are detailed.

With the arises of Industry 4.0, numerous concepts have emerged; one of the main concepts is the digital twin (DT). DT is being widely used nowadays, however, as there are several uses in the existing literature; the understanding of the concept and its functioning can be diffuse. The main goal of this paper is to provide a review of the existing literature to clarify the concept, operation, and main characteristics of DT, to introduce the most current operating, communication, and usage trends related to this technology, and to present the performance of the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.

• A new fuzzy computational model of emotion adapted to the cultural environment. • Emotions and mood defined as vectors in a multidimensional space. • Vector modulus represents the intensity, and the direction represents the emotion. • The Affect Adaptation process updates mood using the Appraised Emotion. • The Affect Adaptation process uses the culture and personality of the agent. Humans use rather vague and imprecise words to express emotions. Therefore, fuzzy logic allows computational affective models to use emotions in the same way that human beings express them. However, people from different cultures and languages assign different meanings to the same emotion word. Unfortunately, there are still no affective computing models that really take these two factors into consideration. In this paper, we propose a fuzzy model of appraisal for multi-agent systems that is adapted to Spanish-speakers. Our methodology has two steps. First, the agent evaluates an event using a set of fuzzy appraisal rules that returns a fuzzy emotion. Then, a defuzzification process returns the Pleasure and Arousal dimensions of the emotion that will be internally represented as a vector in a two-dimensional space. This vector is used to update the agent's mood according to the agent's personality. The agent can express this internal emotional state using a fuzzification process that translates the agent's mood into a fuzzy emotion. This fuzzification process uses the results of an experiment to generate a fuzzy emotion that is adapted to the cultural environment in which the agent is located. This methodology can be easily adapted to other languages. [ABSTRACT FROM AUTHOR]

New systems can be designed, developed, and managed as societies of agents that interact with each other by offering and providing services. These systems can be viewed as complex networks where nodes are bounded rational agents. In order to deal with complex goals, they require cooperation of the other agents to be able to locate the required services. The aim of this paper is formally and empirically analyze under which circumstances cooperation emerges in decentralized search of services. We propose a repeated game model that formalizes the interactions among agents in a search process where agents are free to choose between cooperate or not in the process. Agents make decisions based on the cost of their actions and the expected reward if they participate forwarding queries in a search process that ends successfully. We propose a strategy that is based on random-walks, and we study under what conditions the strategy is a Nash equilibrium. We performed several experiments in order to evaluate the model and the strategy and to analyze which network structures are more appropriate to promote cooperation. [ABSTRACT FROM AUTHOR]

Abstract: In multi-agent systems, agents perform complex tasks that require different levels of intelligence and give rise to interactions among them. From these interactions, conflicts of opinion can arise, especially when these systems become open, with heterogeneous agents dynamically entering or leaving the system. Therefore, agents willing to participate in this type of system will be required to include extra capabilities to explicitly represent and generate agreements on top of the simpler ability to interact. Furthermore, agents in multi-agent systems can form societies, which impose social dependencies on them. These dependencies have a decisive influence in the way agents interact and reach agreements. Argumentation provides a natural means of dealing with conflicts of interest and opinion. Agents can reach agreements by engaging in argumentation dialogues with their opponents in a discussion. In addition, agents can take advantage of previous argumentation experiences to follow dialogue strategies and persuade other agents to accept their opinions. Our insight is that case-based reasoning can be very useful to manage argumentation in open multi-agent systems and devise dialogue strategies based on previous argumentation experiences. To demonstrate the foundations of this suggestion, this paper presents the work that we have done to develop case-based dialogue strategies in agent societies. Thus, we propose a case-based argumentation framework for agent societies and define heuristic dialogue strategies based on it. The framework has been implemented and evaluated in a real customer support application. [Copyright &y& Elsevier]

Abstract: In this article we study the impact of the negotiation environment on the performance of several intra-team strategies (team dynamics) for agent-based negotiation teams that negotiate with an opponent. An agent-based negotiation team is a group of agents that joins together as a party because they share common interests in the negotiation at hand. It is experimentally shown how negotiation environment conditions like the deadline of both parties, the concession speed of the opponent, similarity among team members, and team size affect performance metrics like the minimum utility of team members, the average utility of team members, and the number of negotiation rounds. Our goal is identifying which intra-team strategies work better in different environmental conditions in order to provide useful knowledge for team members to select appropriate intra-team strategies according to environmental conditions. [Copyright &y& Elsevier]

Abstract: The capability of reaching agreements is a necessary feature that large computer systems where agents interoperate must include. In these systems, agents represent self-motivated entities that have a social context, including dependency relations among them, and different preferences and beliefs. Without agreement there is no cooperation and thus, complex tasks which require the interaction of agents with different points of view cannot be performed. In this work, we propose a case-based argumentation approach for Multi-Agent Systems where agents reach agreements by arguing and improve their argumentation skills from experience. A set of knowledge resources and a reasoning process that agents can use to manage their positions and arguments are presented. These elements are implemented and validated in a customer support application. [Copyright &y& Elsevier]

Abstract: Ambient Intelligence aims to offer personalized services and easier ways of interaction between people and systems. Since several users and systems may coexist in these environments, it is quite possible that entities with opposing preferences need to cooperate to reach their respective goals. Automated negotiation is pointed as one of the mechanisms that may provide a solution to this kind of problems. In this article, a multi-issue bilateral bargaining model for Ambient Intelligence domains is presented where it is assumed that agents have computational bounded resources and do not know their opponents’ preferences. The main goal of this work is to provide negotiation models that obtain efficient agreements while maintaining the computational cost low. A niching genetic algorithm is used before the negotiation process to sample one’s own utility function (self-sampling). During the negotiation process, genetic operators are applied over the opponent’s and one’s own offers in order to sample new offers that are interesting for both parties. Results show that the proposed model is capable of outperforming similarity heuristics which only sample before the negotiation process and of obtaining similar results to similarity heuristics which have access to all of the possible offers. [Copyright &y& Elsevier]