Multi Agent Systems Research Papers (original) (raw)

We develop and apply several novel methods quantifying dynamic multi-agent team interactions. These interactions are detected information-theoretically and captured in two ways: via (i) directed networks (interaction diagrams) representing significant coupled dynamics between pairs of agents, and (ii) state-space plots (coherence diagrams) showing coherent structures in Shannon information dynamics. This model-free analysis relates, on the one hand, the information transfer to responsiveness of the agents and the team, and, on the other hand, the information storage within the team to the teamʼs rigidity and lack of tactical flexibility. The resultant interaction and coherence diagrams reveal implicit interactions, across teams, that may be spatially long-range. The analysis was verified with a statistically significant number of experiments (using simulated football games, produced during RoboCup 2D Simulation League matches), identifying the zones of the most intense competition, the extent and types of interactions, and the correlation between the strength of specific interactions and the results of the matches.

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- Information Theory, Complex Systems, Complex Networks, Complex Adaptive Systems

We use an agent-based approach to model trading behaviour in high-frequency markets. This study focuses on the Foreign Exchange (FX) market. The initial part of this study is to observe the micro-behaviour of traders to define the stylized facts of their trading activities. This is performed using a high- frequency dataset of anonymised individual traders' historical transactions on an account

- by Monira Aloud
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- Business, Computational Modeling, Foreign Exchange Market, Agent Based

This paper presents a system proposed for the intelligent management of computer networks. The system is based on the use of Arti cial Intelligence t e chniques | data mining, expert systems and multi-agent systems. The work is based on the following lines of actions: a the use of distributed agents for the intelligent search of information in the network, supplying it in a more abstract way, adapted to the decision-making task; b the use of machine learning and data-mining techniques that, starting from the log les which register previous problems and their solution, allow the use of experience thus obtained in the solution new problems; and c the use of heuristics and conduction rules supplied by experts, through a decision support system, as an advisor element to network operators. This paper presents a discussion about the techniques employed along these three r esearch lines and the results already obtained.

- by Emerson Paraiso and +1
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- Artificial Intelligence, Expert Systems, Decision Making, Machine Learning

Negotiation, an important facet of business, is an iterative and complex process. Depending on the nature of business and the type of transaction, negotiation criteria, duration and complexity vary widely. An intelligent software agent can help the consumers and enterprises in business negotiation. It can negotiate with humans or with other software agents to arrive at mutually agreeable terms and

- by San Murugesan
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- Information Systems, Information Retrieval, Bidding, Intelligent Agent

Despite the advances in argumentation on group decision negotiation there is a need to simulate and identify the personality of participants. To make participants' agents more human-like and to increase their flexibility in the negotiation process in group decision-making, the authors investigated the role of personality behaviours of participants applied to the conflict style theme. The negotiation is made in a bilateral way where both parties are OCEAN participant agents based on the five-factor model of personality (Openness, Conscientiousness, Extraversion, Agreeableness and Negative emotionality).

- by Carlos Dorville Ramos
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- Psychology, Computer Science, Personality, Agent Based

In this paper we present a state of the art review of the soft computing based approaches for trust and reputation computation. We divide the soft computing based approaches for trust and reputation computation into five different... more

- by Elizabeth Chang
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- Fuzzy Logic, Computer Networks, Soft Computing, Neural Networks

E2 is a plugin-based, service-oriented middleware architecture. E2 extends the popular Eclipse platform's idea of building a software system entirely and dynamically from XML-interfaced plugins, adds the feature to remove and replace plugins on the fly, administers the plugin connection process, and provides a message transport plugin for distributed inter-E2 system communication. E2 introduces a generic user interface plugin that separates user interfaces and application functionality. With these extensions, E2 extends the plugin concept, with its success on the desktop, to the broader areas of distributed middleware and multi-agent systems. E2 retains compatibility with Eclipse so that it can reuse Eclipse plugins but also, via an extensible interpreter capability, adds compatibility with Web Services and WSDL. This paper describes the E2 platform, implemented in Java, being used to develop the Everything is Alive agent system.

- by minh vu
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- XML, Software Architecture, User Interface, Middleware

In this project, we extend the work already done in [1.] to include a generalised mathematical framework for studying and explaining the dynamics and behavior of crowds of humans. The method is both analytical and numerical. The numerical methods are used to solve the differential equations of crowds that are derived analytically. The analytical and numerical solutions are compared and their relevance is shown. In this project, we study mainly two types of responses of a crowd: Position Response and Density Response. The latter is formulated using stressors using an approach similar to [2.] which also enables us to derive the General Adaptation Syndrome (GAS) Model in a very generalised form. Finally, we extend stressors to define inter-crowd and intra-crowd interactions using a parameterisation linking it directly to a generalisation of the stressdensity equation. The detailed calculations are done in the later part of this paper. (Refer to Page 21 of this doucument).

Computational intelligent techniques applied to economics have played an important role in the last years. In this paper we propose a framework based on an intelligent conversational agent embedded with a decision support system, aimed at suggesting the best managing strategies for a game-based model of a virtual town. The agent tries to prospect the future evolutions of particular choices taken by the user. Interaction is conducted through a natural language interface built as an Alice-based conversational agent.

Recommender Systems are a class of applications which are used to overcome the problem of information overload. They use the opinions of members of a community to help individuals in that community identify the information most likely to be interesting to them or relevant to their needs, by drawing on user preferences and filtering the set of possible options to a more manageable subset. The key element of such user-support systems is the user model. Traditional techniques used to create user models are usually too rigid to capture the inherent uncertainty of human behavior. Fuzzy sets can handle and process uncertainty in human decision-making and if used in user modeling can be of advantage as it will result in recommendations closely meeting user preferences. In this paper, a hybrid multi-agent recommender system is designed and developed where user's preferences; needs and satisfaction are modeled using interval type-2 (IT2) fuzzy sets. This results in improving the prediction accuracy of the system and hence better recommendations are generated. Experimental study was conducted on book recommender system and promising results were obtained.

- by Pooja Vashisth
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- Computational Modeling, Fuzzy Logic, Fuzzy set theory, Personalization

The initial step of any software engineering methodology is to form requirements. Recently, a goal-oriented approach to requirements has been proposed and argued to be beneficial. Goals also play a key role in the implementation of proactive software agents. However, although some agent-oriented software engineering methodologies have incorporated (aspects of) goal-oriented requirements engineering, and although they target agent platforms that provide goals as an implementation construct, none of the methodologies provide a goal-oriented design process. We present three modifications to the Prometheus methodology which aim to make it more goal-oriented in its design phases: we introduce a goal coupling diagram, as an adjunct to the existing data coupling diagram; we modify the temporal design artefacts to include goals; and we introduce a number of goal-related consistency checks. Finally, we report on an experimental evaluation comparing the effectiveness of the original and refined methodologies.

Formations of multi-agent systems, such as satellites and aircraft, require that individual agents satisfy their kinematic equations while constantly maintaining inter-agent constraints. In this paper, we develop a systematic framework for studying formations of multiagent systems. In particular, we consider undirected formations for centralized formations and directed formations for decentralized formations. In each case, we determine differential geometric conditions that guarantee formation feasibility given the individual agent kinematics. Our framework also enables us to extract a smaller control system that describes the formation kinematics while maintaining all formation constraints.

- by Pedro Lima
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- Distributed Computing, Multiagent Systems, Control Systems, Control system

In this paper, we present a multiagent algorithm for the frequency assignment problem in cellular radio networks. The algorithm, that has been successfully applied to GSM networks, efficiently assigns frequencies to each radio cell... more

- by Alejandro Cortés
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- Engineering, Mathematics, Technology, Multiagent Systems

This paper describes the application of an organic programming language Gaea in programming complex and flexible multi-agent systems. We consider a soccer game as an example. Using organic programming, we can program soccer players in an extended version of a subsumption architecture, called a dynamic subsumption architecture, which is more flexible and efficient than the original one

In open systems where the components, i.e. the agents and the resources, may be unknown at design time, or in dynamic and self-organizing systems evolving with time, there is a need to enable the agents to communicate their intentions with respect to future activities and resource utilization to resolve coordination issues dynamically. Ideally, we would like to allow ad-hoc interaction, where two standalone independently-designed systems are able to coordinate whenever a need arises. The Semantic Web based approach presented in this paper aims at enabling agents to coordinate without assuming any design-time ontological alignment of them. An agent can express an action intention using own vocabulary, and through the process of dynamic ontology linking other agents will be able to arrive at a practical interpretation of that intention. We also show how our approach can be realized on top of the Semantic Agent Programming Language.

- by Vagan Terziyan
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- Resource Allocation, Semantic Web, Software Agents, Ontologies

The problem of evacuating crowded closed spaces, such as discotheques, public exhibition pavilions or concert houses, has become increasingly important and gained attention both from practitioners and from public authorities. A simulation implementation using NetLogo, an agent-based simulation framework that permits the quickly creation of prototypes, is presented. Our aim is to prove that this model developed using NetLogo, albeit simple can be expanded and adapted for fire safety experts test various scenarios and validate the outcome of their design. Some preliminary experiments are carried out, whose results are presented, validated and discussed so as to illustrate their efficiency. Finally, we draw some conclusions and point out ways in which this work can be further extended.

The dynamic conditions of global markets force manufacturers to invest in flexible production strategies to cope with demanding clients and still survive in a competitive economic scenario. In this sense, small series production appears as a trend for many manufacturing niches and brings many challenges regarding manufacturing and quality assurance aspects. Investing in production flexibility implies increasing production control complexity and planning. This flexibility usually does not correlate with higher degrees of manufacturing automation or with quality assurance strategies. The concept of Cognitive Metrology strives for handling the challenging automation and quality inspection requirements of small series production with a new approach based on self-optimizing systems. This paper introduces the concepts of self-optimization and Cognitive Metrology and focuses especially on a multiagent-based approach for supporting flexible automation and quality assurance in small series production, as a basis for the development of the Cognitive Metrology technology. Initial results of the application of this approach into industrial prototypes are introduced and discussed as well as the migration of this system to different industrial scenarios.

- by Jomi Hubner
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- Quality Control, Quality Assurance, Multi Agent Systems, Production Control

Facing new and varied customer's needs, strategies of production have radically changed during these list three decades leading to a need for agile and, as a consequence, self-organized manufacturing control systems. One possible way to integrate self-organization capability is to move from rigid centralized architectures towards distributed architectures. In this paper, we present a state-of-the-art of self-organization models in distributed manufacturing control, according to the bionic, holonic, multi-agent and heterarchical design approaches. We show the potential capabilities offered by these approaches to integrate self-organization mechanisms. Meanwhile, we also point out the insufficiencies of existing contributions, which lead us to highlight some future trends in the design of effective self-organized manufacturing control systems.

This paper provides an agent technology for a decision support system. This system is designed to detect and regulate the traffic of multimodal public transport when many disturbances come simultaneously. The objective of this system is to optimize the regulation action by learning technique of regulator. The goal of this research is to improve the quality of public transport service provided to users and respect the use rules (safety rules, business rules, commercial rules, etc.). So, to improve the quality service of the user, we have to optimize simultaneously several criteria like punctuality, regularity and correspondence in disturbance case. In this paper, we focus primarily on a multi agent system for optimizing and learning of Regulation Support System of a Multimodal Public Transport (RSSPT). We have validated our strategy by simulating situation related to existing transportation system.

A simulation of high-frequency market data is performed with the Genoa Artificial Stock Market. Heterogeneous agents trade a risky asset in exchange for cash. Agents have zero intelligence and issue random limit or market orders depending on their budget constraints. The price is cleared by means of a limit order book. A renewal order-generation process is used having a waiting-time distribution between consecutive orders that follows a Weibull law, in line with previous studies. The simulation results show that this mechanism can reproduce fat-tailed distributions of returns without ad-hoc behavioral assumptions on agents. In the simulated trade process, when the order waiting-times are exponentially distributed, trade waiting times are exponentially distributed. However, if order waiting times follow a Weibull law, analogous results do not hold. These findings are interpreted in terms of a random thinning of the order renewal process. This behavior is compared with order and trade durations taken from real financial data.

- by Silvano Cincotti
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- Microeconomics, Commerce, Multi Agent Systems, Random Processes
- by Eugénio Oliveira and +1
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- Intelligent Agents, Software Agents, Multi Agent Systems, Dynamic Environment

Trust and reputation are central to effective interactions in open multi-agent systems (MAS) in which agents, that are owned by a variety of stakeholders, continuously enter and leave the system. This openness means existing trust and reputation models cannot readily be used since their performance suffers when there are various (unforseen) changes in the environment. To this end, this paper presents FIRE, a trust and reputation model that integrates a number of information sources to produce a comprehensive assessment of an agent's likely performance in open systems. Specifically, FIRE incorporates interaction trust, role-based trust, witness reputation, and certified reputation to provide trust metrics in most circumstances. FIRE is empirically evaluated and is shown to help agents gain better utility (by effectively selecting appropriate interaction partners) than our benchmarks in a variety of agent populations. It is also shown that FIRE is able to effectively respond to changes that occur in an agent's environment.

- by trung huynh
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- Cognitive Science, Multi Agent System, Reputation, Multi Agent Systems

In this paper we present the initial experimental results that we obtained with deploying our distributed agent-based system for Ant Colony Optimization (ACODA) on a computer cluster. The novelty of ACODA consists in agent-based modeling and distribution of the problem environment that is explored by the ants to determine an optimal solution. The effect of this approach is that ants' migration is reduced to asynchronous messages exchanged between the agents that compose the problem environment. The deployment of ACODA on a computer cluster benefits from an automated setup that simplifies the installation and configuration of the necessary software packages.

- by Sorin Ilie
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- Computer Architecture, Ant Colony Optimization, Synchronization, Computers
- by Julita Vassileva
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- Web Intelligence, Reputation, Distributed Processing, Multi Agent Systems

Traffic congestion can be alleviated by infrastructure expansions; however, improving the existing infrastructure using traffic control is more plausible due to the obvious financial resources and physical space constraints. The most promising control tools include ramp metering, variable message signs, and signalized intersections. Synergizing the aforementioned strategies in one platform is an ultimate and challenging goal to alleviate traffic gridlock and optimally utilize the existing system capacity; this is referred to as Integrated Traffic Control (ITC). Reinforcement Learning (RL) techniques have the potential to tackle the optimal traffic control problem. Game Theory (GT) fits well in modelling the distributed control systems as multi-player games. Multi-Agent Reinforcement Learning (MARL) achieves the potential synergy of RL and GT concepts, providing a promising tool for optimal distributed traffic control. The objective of this paper is to clarify the opportunities of game theory concepts and MARL approaches in creating an adaptive optimal traffic control system that is decentralized but yet integrated through agents' interactions. In this paper, we comparatively review and evaluate the relevant existing approaches. We then envision and introduce a novel framework that combines GT concepts and MARL to achieve a Multi-Agent Reinforcement Learning for Integrated Network of Optimal Traffic Controllers (MARLIN-OTC).

- by Samah El-Tantawy
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- Game Theory, Reinforcement Learning, Multi Agent Systems

Abstract This paper introduces a multi-agent framework for distributed multiplayer game development and simulations. The framework allows the incorporation and experimentation with different strategies of the Players, possibly including intelligent behaviors. The framework consists of a set of generic agent types that must be specialized and configured for a specific game. The framework uses a generic agent that enforces the rules of the game, as well as generic bot-agents that represent the game Players. To support our claims of ...

- by Sorin Ilie
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- Computer Architecture, Agent Based, User Interface, Multi Agent System

In this paper, we present our methodology proposal for cooperative remote systems modeling. Its aim is to develop models of existing or planned cooperative systems. These models are used to specify systems or to create dynamic working simulations. Comparative performances are deduced from the latter. The associated meta-model proposal is based, among other things, on the use of multi-agent systems, Petri nets and stochastics Petri nets. After having described the whole methodology concepts, we show a set of general results extracted from simulations.

- by N. Zerhouni
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- Distributed Computing, Multiagent Systems, Computational Modeling, Petri Nets

Agreement technologies have settled the basis for creating systems that operate on the basis of agreements in societies of independent, autonomous computational entities (agents). However, nowadays more and more systems of such kind rely on a seamless interaction of software agents with humans. Humans work in partnership (directly or indirectly) or closely related with agents that are able to act autonomously and intelligently. Specifically, humans and agents have the ability to establish a series of relationships/collaborative interactions with each other, forming what might be called human-agent teams to meet their individual or collective goals within an organisation or social structure. Systems in which people and agents operate on a large scale offer an enormous potential but also require the consideration of additional issues. In this paper we analyse the open issues that may be addressed for researches in order to develop open human-agent systems. We present a real-world case study and an abstract architecture proposal for such systems. 1 Introduction Nowadays more and more humans work in partnership (directly or indirectly) or closely related with computational entities (agents) that are able to act autonomously and intelligently. Considering systems of people and agents operating on a large scale offers an enormous potential and, if performed properly, it will help tackle complex social applications. As intelligent computational systems pervade the human space, they dramatically change the ways in which human users interact with technological systems. Rather than performing tasks in an isolated and subordinate fashion, computational agents are involved in an increasing range of collaborative relationships with humans, where negotiation and task delegation occur along the agent-agent axis as well as along the human-agent one. Due to its social ground, agreement technologies can be the basic driver to smooth the boundary between the human space and the computational space so as to create cooperative social ensembles of humans and agents that work in strict

- by Juan M Corchado
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- Multi Agent Systems, Human-agent societies

The paper presents a semantic logging framework which allows structured information logging in an agent-based distributed system for chemical incident response. The logging framework is "semantic" because it allows semantic interpretation of logs according to relationships defined between logging events. For example, this approach could help the reconstruction of the order of events that occurred during the response to an incident, thus giving a detailed view of system execution trace, as well as of agents' decisions taken at various decision points during the incident management workflow. We intend to use semantic logs (i) for helping experts to analyze and explain system actions and thus improving system response to future incidents, as well as (ii) for training stakeholders by setting the system to run replaylike simulations of past incident management workflows. Sorin Ilie, Mihnea Scafeş, Costin Bȃdicȃ, Thomas Neidhart, and Rani Pinchuk were supported by DIADEM project. Diadem project is funded by European Union under Information and Communication Technologies (ICT) theme of the 7th Framework Programme for R&D, ref. no: 224318. 1. DIADEM project -Distributed information acquisition and decisionmaking for environmental management: http://www.ist-diadem.eu/ -265 -978-1-4244-7433-2/10/$26.00 ©2010 IEEE

- by Sorin Ilie
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- Software Engineering, Multiagent Systems, Agent Based, Environmental Management

This paper provides an overview of research and development activities in the field of autonomous agents and multi-agent systems. It aims to identify key concepts and applications, and to indicate how they relate to one-another. Some historical context to the field of agent-based computing is given, and contemporary research directions are presented. Finally, a range of open issues and future challenges are highlighted.

- by Michael Wooldridge
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- History, Cognitive Science, Multi Agent System, Autonomous Agents

Developing Poker agents that can compete at the level of a human expert can be a challenging endeavor, since agents' strategies must be capable of dealing with hidden information, deception and risk management. A way of addressing this issue is to model opponents' behavior in order to estimate their game plan and make decisions based on such estimations. In this paper, several hand evaluation and classification techniques are compared and conclusions on their respective applicability and scope are drawn. Also, we suggest improvements on current techniques through Monte Carlo sampling. The current methods to deal with risk management were found to be pertinent concerning the agent's decision-making process; nevertheless future integration of these methods with opponent modeling techniques can greatly improve overall Poker agents' performance.

- by Luis Paulo Reis
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- Computer Science, Computational Modeling, Risk Management, Monte Carlo Methods

Automata-based approach, proposed for the programming of the virtual autonomous reactive agents control systems used in the famous "Robocode" game is extended in this paper to the creation of the control systems of the reactive multi-agent real-life environment agents. We demonstrate the efficiency of the proposed approach by the example of creation of transportation system, which consists of two interacting robots and is assembled from the famous "Lego Mindstorms" kit. The advantage of this approach is the formalization of the implementation process and the simplification of testing and modification.

- by Anatoly Shalyto
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- Control system, LEGO Mindstorms, Mobile Robots, Multi Agent Systems

In this paper, we analyze a model of capacity sharing for a set of independent firms, geographically distributed, that often have to implement an opportune tool to integrate their resources and demand forecasts in order to gather a specific production objective. We formulate the problem as a cooperative game and identify a capacity sharing solution using the Gale-Shapley model. The allocation rule takes into account the utility functions of the involved firms, and we show how the capacity allocation rule can be designed to induce all firms to report truthfully their information. Moreover, we show that, under this allocation rule, truth telling is a dominant strategy, with each firm reporting truthfully its private information, regardless of the reporting decisions of other firms. Moreover, the proposed research develops a distributed approach able to facilitate the capacity sharing process by using a multi-agent architecture; then a discrete simulation environment has been developed to compare the proposed approach with a centralized one. Several simulation scenarios were conducted to analyze the performances' trends in various environment conditions.

- by Paolo Renna
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- Engineering, Game Theory, Mathematical Sciences, Multi Agent Systems

The feasibility of using a motion sensor to replace a conventional electrolarynx (EL) user interface was explored. A mobile phone motion sensor with multi-agent platform was used to investigate on/off and pitch frequency control capability. A very small battery operated ARM-based control unit was also developed to evaluate the motion sensor based user-interface. The control unit was placed on the wrist and the vibration device was placed against the throat using support bandage. Two different conversion methods were used for the forearm tilt angle to pitch frequency conversion: linear mapping method and F0 template-based method. A perceptual evaluation was performed with two well-trained normal speakers and ten subjects. The results of the evaluation study showed that both methods were able to produce better speech quality in terms of naturalness.

- by Alberto Pérez
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- Agents, Prosody, Multi Agent Systems, Electrolarynx

This paper proposes a new approach for creating conversation-based natural language interfaces to relational databases by combining goal oriented conversational agents and knowledge trees. Goal oriented conversational agents have proven their capability to disambiguate the user's needs and to converse within a context (i.e. specific domain). Knowledge trees used to overcome the lacking of connectivity between the conversational agent and the relational database, through organizing the domain knowledge in knowledge trees. Knowledge trees also work as a road map for the conversational agent dialogue flow. The proposed framework makes it easier for knowledge engineers to develop a reliable conversation-based NLI-RDB. The developed prototype system shows excellent performance on common queries (i.e. queries extracted from expert by a knowledge engineer). The user will have a friendly interface that can converse with the relational database.

This paper presents a concrete way of linking the JADE multi-agent system with the equipment (eg PLC, DCS, SCADA, HMI) comprised into a distributed industrial control system based on agents, using OPC servers. The differences between traditional control and agent based control approach also briefly showed. Industrial applications of multi-agent technology are limited, among others, especially due to the difficulties of communication between agents development environments and heterogeneous set of control devices, sensors and actuators which can be found in an industrial process. The solution involved the use of OPC standard. By using an OPC client written in Java, the connection between JADE multi-agent system development also written in Java, and OPC servers, was made; that allow access from JADE agent to process variables. The concrete steps for developing a JADE agent with the ability to connect it to the OPC server were presented. The content of this paper refers to a part of a dedicated application for monitoring, collection and archiving data of a manufacturing process in the automotive industry. The data are used by the maintenance planning system for carrying out checks and repairs on monitored equipment and machinery according to real functioning duration.

- by Eugen Diaconescu
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- Process Control, Planning, Sensors, Actuators

In software engineering community an increasing effort has been put into design and development of multiagent systems (MAS). However, agent system development is currently dominated by informal guidelines, heuristics and inspirations rather than formal principles and well defined engineering techniques. In this paper we define a set of objective and subjective metrics to measure the complexity of MAS. The subjective metrics is a modified version of function Point (FP) including the algorithmic complexity and knowledge complexity factor. The objective metrics is a measure for nearly-decomposability, measured by the communicative cohesion. Such metrics can be used to select the best architecture for the MAS. A methodology for agent-based software development based on such metrics is proposed.

- by Tom Wanyama
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- Computer Architecture, Software Engineering, Multiagent Systems, Software Development

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

- by Carlos Dorville Ramos
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- Computer Science, Game Theory, Data Mining, Data Analysis

In this paper, a novel radio resource scheduling policy for Long Term Evolution Advanced (LTE-A) radio access technology in downlink acceptance is proposed. The scheduling process works with dispatching rules which are various with different behaviors. In the literature, the scheduling disciplines are applied for the entire transmission sessions and the scheduler performance strongly depends on the exploited discipline. Our method provides a straightforward schedule within transmission time interval (TTI) frame. Hence, a mixture of disciplines can be used for each TTI instead of the single one adopted across the whole transmission. The grand objective is to bring real improvements in terms of system throughput, system capacity and spectral efficiency (operator benefit) assuring in the same time the best user fairness and Quality of Services (QoS) capabilities (user benefit). In order to meet this objective, each rule must to be called on the best matching conditions. The policy adoption and refinement are the best way to optimize the use of mixture of rules. The Q-III reinforcement learning algorithm is proposed for the policy adoption in order to transform the scheduling experiences into a permanent nature, facilitating the decision-making on which rules will be used for each TTI. The IQ-III reinforcement learning algorithm using multiagent environments refines the policy adoption by considering the agents' opinions in order to reduce the policy convergence time.

- by Mehmet Emin Aydin
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- Mobile Computing, Multi Agent Systems, Quality of Service

To meet changing needs of customers and to survive in the increasingly globalised and competitive environment, it is necessary for companies to equip themselves with intelligent tools, thereby enabling managerial levels to use the tactical decision in a better way. However, the implementation of an intelligent system is always a challenge in Small-and Medium-sized Enterprises (SMEs). Therefore, a new and simple approach with 'process rethinking' ability is proposed to generate ongoing process improvements over time. In this paper, a roadmap of the development of an agent-based information system is described. A case example has also been provided to show how the system can assist non-specialists, for example, managers and engineers to make right decisions for a continual process improvement. , W. (2006) 'Design and development of an agent-based information system for process improvement', Int.

- by Bill Chan
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- Information Systems, Smes, Information Technology Management, Multi Agent Systems

Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

- by Andrew Reeson and +1
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- Decision Making, Ecological Economics, Ecology, Multidisciplinary

This paper proposes a new approach for the problem of allocating production capacity to multiple requirements, based on the Multi-Agents paradigm. The proposed system is a distributed, decentralised system that presents many advantages over the traditional centralised algorithms. Among the others it is more #exible, more reactive, and easily understandable. Moreover, a prototype of personal digital assistant is described. Such an assistant is able to support distributed decision-making in companies where several product lines compete for the same resources, in a contest of swiftly changing and scarcely foreseeable demand.

- by Alessandro Brun
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- Negotiation, Distributed System, Multidisciplinary, Distributed Systems

A multiagent-based Distribution Automation System (DAS) is developed for service restoration of distribution systems after a fault contingency. In this system, Remote Terminal Unit (RTU) agents, Main Transformer (MTR) agents, Feeder Circuit Breaker (FCB) agents, and Feeder Terminal Unit (FTU) agents of the Multiagent System (MAS) are used to derive the proper restoration plan after the faulted location is identified and isolated. To assure the restoration plan complies with operation regulation, heuristic rules based on standard operation procedures of Taipower's distribution system are included in the best first search of the MAS. For fault contingency during summer peak season when the capacity reserves of supporting feeders and main transformer are not enough to cover the fault restoration, load shedding scheme is derived for the MAS to restore service to as many key customers and loads as possible. A Taipower distribution system with 43 feeders is selected for computer simulation to demonstrate the effectiveness of the proposed methodology. The results show that by applying the proposed multiagent-based DAS, service of distribution systems can be efficiently restored.

- by Chung-sheng Li
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- Multiagent Systems, Fault Detection, Distributed System, Applications

Applications of artificial intelligence in cyber warfare have been mainly postulated and studied in the context of defensive operations. This paper provides an introductory overview of the use of autonomous agents in offensive cyber warfare, drawing on available open literature. The study supplies an introduction to the taxonomy and science underlying intelligent agents and their strengths and weaknesses: the technological elements that autonomous agents should include are explained, as well as the economics involved. The paper also aims to explore possible legal implications of the use of autonomous agents and shows how they could fit into the legal context of warfare. The conclusion of the study is that the use of AI technologies will be an important part of cyber offensive operations, from both the technological and the economical aspects; however, the legal and doctrinal landscape is still uncertain and proper frameworks are still to be developed.

- by Alessandro Guarino
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- Computer Science, Artificial Intelligence, Law, International Law

The development trend of computing is that the intelligence will become ambient. It is a one-user multi-device paradigm. These devices are transparent to the user and they can react in a proactive and non- intrusive manner. Moreover, among the general population those most likely to benefit from the development of this technology are the elderly and dependent people. They often wish to continue living independently in their home as opposed to being forced to live in a hospital. For that, homes should be smart in order to provide safety, security to reduce falls, disability, stress, fear or social isolation. Nevertheless, much of processes used for smart home design are ad-hoc. To cope with this drawback, while taking into account both dimensions of time and space, it is required to use a suitable formal model that is able to handle smart home domain specific nature. This paper proposes a technique that uses reference nets to model and simulate a smart home which is sensitive, adapti...

- by sara kerraoui
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- Elderly, Multi Agent Systems, Smart Home

The paper provides an overview of the agent-based solutions developed by the Rockwell Automation company for the purposes of industrial control. Using agent-based manufacturing control, a higher degree of flexibility and reconfigurability of manufacturing solutions as well as higher robustness of the industrial systems can be achieved. Specific solutions connected with the proposed agent architecture, with implementation of the real-time control agents as well as with the information transfer among the SW agents and the real-time agents in a Programmable Logic Controller (PLC) are presented. Attention is also paid to the simulation of both the agent-based manufacturing facilities and their control systems. A simulation environment MAST for material handling systems has been implemented in JADE. The opportunity to re-use directly the simulation software on the agent control level is one of the most important features of MAST.

- by Francisco Maturana
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- Manufacturing, Agent Based, Control system, Multi Agent System

This paper presents an approach based on a multi agent system vision for the resolution of the problem of university timetable. This problem is very important. Indeed a bad schedule affects negatively affects the level of student acquisition. This problem is an arduous problem whose handmade achievement is a drastic task that can mobilize several people several days of work without any guarantee on the quality of the found solutions. The proposed approach involves agents to find timetables that constitute a compromise of a multitude of points of view. Each agent works on behalf of a teaching actor. After a first phase where all the possible timetables are generated, a second phase is executed in the form of several iterations. In each cycle, each agent eliminates the least preferred schedule among possible schedules. Thus, it remains timetables that represent compromises between all agents and therefore the teaching actors.

In this paper, we propose a novel, secure, and intelligent IoT approach based on agent, we have implemented in the health care domain, where we developed an intelligent patient monitoring system for monitoring the patients heart rate automatically. Our system is more intelligent that can anticipate the critical condition before it even happens, send a message to the patient family, doctors, nurses, as well as hospital in-charge personal, and launch an alarm to be assisted by the nearest people in place. Also, our architecture ensures the authentication, authorization, and data sensing confidentiality. Hospitals and medical clinics can utilize our system to monitor their outpatients who are in danger of unpredictable health conditions. The approach presented in the paper can also be applied to other IoT domains.

- by Abdelhak Merizig
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- Computer Science, Artificial Intelligence, Structural Health Monitoring, Health