Foundations of distributed interaction systems

There are numerous applications where a variety of human and software participants interactively pursue a given task (play a game, engage in a simulation, etc.). In this paper, we define a basic architecture for a distributed, interactive system (DIS for short). We then formally define a mathematical construct called a DIS abstraction that provides a theoretical basis for a software platform for building distributed interactive systems. Our framework provides a language for building multiagent applications where each agent has its own behaviors and where the behavior of the multiagent application as a whole is governed by one or more “master” agents. Agents in such a multiagent application may compete for resources, may attempt to take actions based on incorrect beliefs, may attempt to take actions that conflict with actions being concurrently attempted by other agents, and so on. Master agents mediate such conflicts. Our language for building agents (ordinary and master) depends critically on a notion called a “generalized constraint” that we define. All agents attempt to optimize an objective function while satisfying such generalized constraints that the agent is bound to preserve. We develop several algorithms to determine how an agent satisfies its generalized constraints in response to events in the multiagent application. We experimentally evaluate these algorithms in an attempt to understand their advantages and disadvantages. This revised version was published online in June 2006 with corrections to the Cover Date.     

Multiagent immediate incremental view maintenance for data warehouses

Data warehouse systems typically designate downtime for view maintenance, ranging from tens of minutes to hours depending on the system size. We develop a multiagent system that achieves immediate incremental view maintenance (IIVM) for continuous updating of data warehouse views. We describe an IIVM system that processes updates as transactions are executed at the underlying data sources to eliminate view maintenance downtime for the data warehouse-a crucial requirement for internet applications. The use of a multiagent framework provides considerable process speed improvement when compared with other IIVM systems. Since agents are used to delegate the data sources and warehouse views, it is easy to reorganize the components of the system. Through the use of cooperative agents, the data consistency of IIVM can be easily maintained. The test results from this research show that the proposed system increases the availability of the data warehouse while preserving a stringent requirement on data consistency.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

ASPECS: an agent-oriented software process for engineering complex systems

Holonic multiagent systems (HMAS) offer a promising software engineering approach for developing complex open software systems. However the process of building Multi-Agent Systems (MAS) and HMAS is mostly different from the process of building more traditional software systems as it introduces new design and development challenges. This paper introduces an agent-oriented software process for engineering complex systems called ASPECS. ASPECS is based on a holonic organisational metamodel and provides a step-by-step guide from requirements to code allowing the modelling of a system at different levels of details using a set of refinement methods. This paper details the entire ASPECS development process and provides a set of methodological guidelines for each process activity. A complete case study is also used to illustrate the design process and the associated notations. ASPECS uses UML as a modelling language. Because of the specific needs of agents and holonic organisational design, the UML semantics and notation are used as reference points, but they have been extended by introducing new specific profiles.     

Engineering open environments with electronic institutions

Nowadays, with the expansion of Internet, there is a need of methodologies and software tools to ease the development of applications where distributed homogeneous entities can participate. Multiagent systems, and electronic institutions in particular, can play a main role in the development of this type of systems. Electronic institutions define the rules of the game in agent societies, by fixing what agents are permitted and forbidden to do and under what circumstances. The goal of this paper is to present EIDE, an integrated development environment for supporting the engineering of multiagent systems as electronic institutions.     

Supporting communication and cooperation in distributed representation for adaptive design

Different types of graphs has been successfully used to represent designs at different stages of the design process. Changes to a model representing a design during the process can be modelled by applying graph transformations. In many real life design tasks the changes/updates can be carried out simultaneously on different parts of the design. Hence a model based on graph transformations is coupled with a multiagent paradigm to enable the parallelisation of these transformations to mimic the real life approach. In this paper a hypergraph representation and transformation model is used as a basis for building a multiagent system supporting distribution and adaptation in computer aided design. This representation can be applicable throughout the lifecycle of the design. It is based on research in formal language theory, like graph grammars, and distributed models including multiagent systems. The motivation for the work presented here is given and possible applications are described. The application of the theoretical results in a graph distribution toolkit proposed as a multiagent framework is also considered. To assure the efficiency of the system it should be implemented as a parallel multiagent system. The hypergraph distribution and partial replication, allowing for its parts to be managed by agents, is also presented. The approach is illustrated by a case study from the domain of building design, where it is used to represent, modify and maintain building information.     

TRAMMAS: A tracing model for multiagent systems

Agent's flexibility and autonomy, as well as their capacity to coordinate and cooperate, are some of the features which make multiagent systems useful to work in dynamic and distributed environments. These key features are directly related to the way in which agents communicate and perceive each other, as well as their environment and surrounding conditions. Traditionally, this has been accomplished by means of message exchange or by using blackboard systems. These traditional methods have the advantages of being easy to implement and well supported by multiagent platforms; however, their main disadvantage is that the amount of social knowledge in the system directly depends on every agent actively informing of what it is doing, thinking, perceiving, etc. There are domains, for example those where social knowledge depends on highly distributed pieces of data provided by many different agents, in which such traditional methods can produce a great deal of overhead, hence reducing the scalability, efficiency and flexibility of the multiagent system. This work proposes the use of event tracing in multiagent systems, as an indirect interaction and coordination mechanism to improve the amount and quality of the information that agents can perceive from both their physical and social environment, in order to fulfill their goals more efficiently. In order to do so, this work presents an abstract model of a tracing system and an architectural design of such model, which can be incorporated to a typical multiagent platform.     

Declarative representations of multiagent systems

This paper explores the specification and semantics of multiagent problem-solving systems, focusing on the representations that agents have of each other. It provides a declarative representation for such systems. Several procedural solutions to a well-known test-bed problem are considered, and the requirements they impose on different agents are identified. A study of these requirements yields a representational scheme based on temporal logic for specifying the acting, perceiving, communicating, and reasoning abilities of computational agents. A formal semantics is provided for this scheme. The resulting representation is highly declarative, and useful for describing systems of agents solving problems reactively     

Evidentialist foundationalist argumentation for multi-agent sensor fusion

In this paper, an approach to evidence-based argumentation called Evidentialist Foundationalist Argumentation (EFA) is formally defined in terms of the ASPIC framework. The EFA framework is then used as the basis for general argument patterns applied to the problem domain of Sensor Fusion. These general Sensor Fusion argument patterns serve as templates for concrete arguments constructed by agents in an in situ Sensor Web. These agents use EFA to solve specific instances of the Decentralized Sensor Fusion problem by strategically sharing evidence from their arguments using a Share on Disagreement protocol. Using real-world data, the performance of this multiagent system is compared to the performance of another multiagent system employing a Kalman Filtering approach. The results are statistically analyzed using omega-squared effect sizes produced by ANOVA with p values <  0.05. The EFA based system is found to outperform the Kalman Filtering system in terms of accuracy with mostly high and medium effect sizes. The Kalman Filtering system is found to outperform the EFA based system in terms of communication costs with mostly low effect sizes.     

A Computational Framework for Practical Social Reasoning

This article describes a framework for practical social reasoning designed to be used for analysis, specification, and implementation of the social layer of agent reasoning in multiagent systems. Our framework, called the expectation strategy behavior (ESB) framework, is based on (i) using sets of update rules for social beliefs tied to observations (so‐called expectations), (ii) bounding the amount of reasoning to be performed over these rules by defining a reasoning strategy, and (iii) influencing the agent's decision‐making logic by means of behaviors conditioned on the truth status of current and future social beliefs. We introduce the foundations of ESB conceptually and present a formal framework and an actual implementation of a reasoning engine, which is specifically combined with a general (belief–desire–intention‐based) practical reasoning programming system. We illustrate the generality of ESB through select case studies, which show that it is able to represent and implement different typical styles of social reasoning. The broad coverage of existing social reasoning methods, the modularity that derives from its declarative nature, and its focus on practical implementation make ESB a useful tool for building advanced socially reasoning agents.     

Safety and Security in Multiagent Systems: Report on the 2nd SASEMAS workshop (SASEMAS'05)

As intelligent autonomous agents and multiagent systems' applications become more pervasive, it becomes increasingly more important to understand the risks associated with using these systems. Incorrect or inappropriate agent behaviour can have harmful effects including financial cost, loss of data, and injury to humans or systems. Thus, security and safety are two central issues when developing and deploying such systems.However, the process of developing safe and secure multiagent systems, and verifying and validating them, is much more difficult than for conventional software systems. This is due to many agent-related aspects, such as the complex and rich multiagent environments, the risks involved in such environments, and the characteristics that can be found in agent systems such as learning, dynamic reacting and adapting. Hence, new and different techniques and perspectives are required to assist with the development and deployment of such systems.The Safety and Security in Multiagent Systems (SASEMAS) workshop presents new developments, and lessons learned from real world cases, and it provides a forum for the exchange of ideas and discussion on areas related to security and safety in multiagent systems.     

Toward a systems- and control-oriented agent framework.

This paper develops a systems- and control-oriented intelligent agent framework called the hybrid intelligent control agent (HICA), as well as its composition into specific kinds of multiagent systems. HICA is essentially developed around a hybrid control system core so that knowledge-based planning and coordination can be integrated with verified hybrid control primitives to achieve the coordinated control of multiple multimode dynamical systems. The scheme is applied to the control of teams of unmanned air and ground vehicles engaged in a pursuit-evasion war game. Results are demonstrated in simulation.     

FAME: A UML-based framework for modeling fuzzy self-adaptive software

Context: Software Fuzzy Self-Adaptation (SFSA) is a fuzzy control-based software self-adaptation paradigm proposed to deal with the fuzzy uncertainty existing in self-adaptive software. However, as many software engineers lack fuzzy control knowledge, it is difficult for them to design and model this kind of fuzzy self-adaptive software (F-SAS). Therefore, efficient and effective modeling technologies and tools are needed for the SFSA framework.Objective: This paper aims to identify modeling requirements of F-SAS and to provide a modeling framework to specify, design and model F-SAS systems. Such a framework can simplify modeling process of F-SAS and improve the accessibility of software engineers to the SFSA paradigm.Method: This study proposes a modeling framework called Fuzzy self-Adaptation ModEling (FAME). By extending UML, FAME creates three types of modeling views. An analysis view called Fuzzy Case Diagram is created to specify the fuzzy self-adaptation goal and the realization processes of this goal. A structure view called Fuzzy Class Diagram is created to describe the fuzzy concepts and structural characteristics of F-SAS. A behavior view called Fuzzy Sequence Diagram is created to depict the dynamic behaviors of the F-SAS systems. The framework is implemented as a plug-in of Enterprise Architect.Results: We demonstrate the effectiveness and efficiency of the proposed approach by carrying out a subject-based empirical evaluation. The results show that FAME framework can improve modeling quality of F-SAS systems by 44.38% and shorten modeling time of F-SAS systems by 38.41% in comparison with traditional UML. Thus, FAME can considerably ease the modeling process of F-SAS systems.Conclusion: FAME framework incorporates the SFSA concepts into standard UML. Therefore, it provides a direct support to model SFSA characteristics and improves the accessibility of software engineers to the SFSA paradigm. Furthermore, it behaves a good example and provides good references for modeling domain-specific software systems.     

Distributed robust stabilization of networked multiagent systems with strict negative imaginary uncertainties

This paper deals with the distributed robust stabilization problem for networked multiagent systems with strict negative imaginary (SNI) uncertainties. Communication among agents in the network is modelled by an undirected graph with at least one self‐loop. A protocol based on relative state measurements of neighbouring agents and absolute state measurements of a subset of agents is considered. This paper shows how to design the protocol parameters such that the uncertain closed‐loop networked multiagent system is robustly stable against any SNI uncertainty within a certain set for various different network topologies. Tools from negative imaginary (NI) theory are used as an aid to simplify the problem and synthesise the protocol parameters. We show that a state, input, and output transformation preserves the NI property of the network. Consequently, a necessary and sufficient condition for the transfer function matrix of the nominal closed‐loop networked system to be NI and satisfy a DC gain condition is that multiple reduced‐order equivalent systems be NI and satisfy a DC gain condition simultaneously. Based on the reduced‐order systems, we derive sufficient conditions in an LMI framework which ensure the existence of a protocol satisfying the desired objectives. A numerical example is given to confirm the effectivenesses of the proposed results.     

Multiagent based differential evolution approach to optimal power flow

This paper proposes a new differential evolution approach named as multiagent based differential evolution (MADE) based on multiagent systems, for solving optimal power flow problem with non-smooth and non-convex generator fuel cost curves. This method integrates multiagent systems (MAS) and differential evolution (DE) algorithm. An agent in MADE represents an individual to DE and a candidate solution to the optimization problem. All agents live in a lattice like environment, with each agent fixed on a lattice point. In order to obtain optimal solution quickly, each agent competes and cooperates with its neighbors and it can also use knowledge. Making use of these agent-agent interaction and DE mechanism, MADE realizes the purpose of minimizing the value of objective function. MADE applied to optimal power flow is evaluated on 6 bus system and IEEE 30 bus system with different generator characteristics. Simulation results show that the proposed method converges to better solutions much faster than earlier reported approaches.     

Environment as a first class abstraction in multiagent systems

The current practice in multiagent systems typically associates the environment with resources that are external to agents and their communication infrastructure. Advanced uses of the environment include infrastructures for indirect coordination, such as digital pheromones, or support for governed interaction in electronic institutions. Yet, in general, the notion of environment is not well defined. Functionalities of the environment are often dealt with implicitly or in an ad hoc manner. This is not only poor engineering practice, it also hinders engineers to exploit the full potential of the environment in multiagent systems. In this paper, we put forward the environment as an explicit part of multiagent systems.We give a definition stating that the environment in a multiagent system is a first-class abstraction with dual roles: (1) the environment provides the surrounding conditions for agents to exist, which implies that the environment is an essential part of every multiagent system, and (2) the environment provides an exploitable design abstraction for building multiagent system applications. We discuss the responsibilities of such an environment in multiagent systems and we present a reference model for the environment that can serve as a basis for environment engineering. To illustrate the power of the environment as a design abstraction, we show how the environment is successfully exploited in a real world application. Considering the environment as a first-class abstraction in multiagent systems opens up new horizons for research and development in multiagent systems.     

Multiagent simulation of protection of information resources in internet

An approach to investigation of mechanisms of protection of information resources on the Internet based on multiagent simulation is proposed. According to this approach, protection systems are considered as interacting teams of intellectual agents. The architecture and program implementation of the simulation environment providing a possibility of integration of simulation on the basis of discrete events, multiagent approach, and simulation of network packet exchange using different Internet protocols are presented. The developed environment provides a possibility of analysis of complex attack scenarios and defense mechanisms. Experimental results on investigation of cooperative mechanisms of defense from “Distributed Denial of Service” attacks are presented. The promising character of realization of these mechanisms for defense from distributed attacks on the Internet is demonstrated.