A multiagent telemedicine system

In this paper we propose a telemedicine sytem model based on multiagent systems. Then, we develop a simulator based on this model. The system is composed of seven agents, such as: a medical database management agent, an application agent, and a planning agent. Some simulations are presented to evaluate the performance of our system. The simulator was developed using JAFMAS (Java-based Agent Framework for Multiagent Systems).     

CRAFTING THE MIND OF PROSOCS AGENTS

PROSOCS agents are software agents that are built according to the KGP model of agency. KGP is used as a model for the mind of the agent, so that the agent can act autonomously using a collection of logic theories, providing the mind's reasoning functionalities. The behavior of the agent is controlled by a cycle theory that specifies the agent's preferred patterns of operation. The implementation of the mind's generic functionality in PROSOCS is worked out in such a way so it can be instantiated by the platform for different agents across applications. In this context, the development of a concrete example illustrates how an agent developer might program the generic functionality of the mind for a simple application.     

A privacy-preserving model for multi-agent propositional planning

Abstract

Over the last years, the planning community has formalised several models and approaches to multi-agent (MA) propositional planning. One of the main motivations in MA planning is that some or all agents have private knowledge that cannot be communicated to other agents during the planning process and the plan execution. We argue that the existing models of the multi-agent planning task do not maintain the agents’ privacy when a (strict) subset of the involved agents share confidential knowledge, or when the identity/existence of at least one agent is confidential. In this paper, first we propose a model of the MA-planning tasks that preserves the privacy of the involved agents when this happens. Then we investigate an algorithm based on best first search for our model that uses some new heuristics providing a trade-off between accuracy and agents’ privacy. Finally, an experimental study compares the effectiveness of using the proposed heuristics.     

Using mobile agents to support interorganizational workflow management

This article argues that the mobile agent approach is well suited for sporadic communication in open distributed systems, especially for rather ''loose'' cooperations across local and organizational boundaries. In an increasing number of cases, management of distributed business procedures reaches beyond such boundaries. This means, for most existing workflow management systems, that cooperating partners are required to give up their local autonomy. However, for cases in which business partners intend to cooperate but still need to preserve their local autonomy, process participation on the basis of mobile agents represents an appropriate mechanism. This article shows how such process integration can be achieved. It also demonstrates how the Common Open Service Market (COSM) system software can be extended in order to use petri-net based process definitions that realize mobile agents in an integrated distributed system platform.     

Verifying plans for multiple agents

Abstract

Research in distributed artificial intelligence planning has historically focused on two distinct classes of problems. One paradigm has been that of 'planning for multiple agents', which considers issues inherent in centrally directed multi-agent execution. The second paradigm has been 'distributed planning', where multiple agents more autonomously participate in coordinating and deciding upon their own actions. The work described in this paper is in the first category, planning for multiple agents. Taking the STRIPS representation of actions, and directed acrylic graphs (DAGs) as plan representations particularly well suited to parallel execution, it formally analyses the following question: how can a DAG plan be verified (i.e. how can we be sure such a plan will be correct, given our uncertainty about exactly when unconstrained parallel actions will be performed)? A method is presented for verifying the correctness of plans for multiple agents, represented as DAGs. The technique allows for the efficient analysis of a plan, despite its many potential execution histories.     

On the sources of complexity in agent design

This article addresses the question of what makes agent design hard. This is a fundamental issue not just for the intelligent agents community, but also for the computer science and software engineering communities in general. The article begins by presenting a simple, informal model of agents and their environments, and then uses this model to frame a discussion on the sources of complexity in agent design. Three key sources of complexity are identified: the agent's environment, the nature of interaction between agent and environment, and the nature of the specification or task for the agent. Following this discussion, the article presents a simple formal model of agents and their environments, which is capable of representing many of these sources of complexity. Using the formal model, a number of stereotypical agent design problems are defined. The article concludes with a discussion of related work and issues.     

Composing web services enacted by autonomous agents through agent-centric contract net protocol

ContextAgents are considered as one of the fundamental technologies underlying open and dynamic systems that are largely enabled by the semantic web and web services. Recently, there is a trend to introduce the notion of autonomy empowered by agents into web services. However, it has been argued that the characteristics of autonomy will make agents become available intermittently and behave variedly over time, which therefore increase the complexity on devising mechanisms for composing services enacted by autonomous agents.ObjectiveIn this work, we propose an extension to Contract Net protocol, called Agent-centric Contract Net Protocol (ACNP), as a negotiation mechanism with three key features for composing web services enacted by autonomous agents.Method(1) A matchmaking mechanism embedded in a middle agent (as a service matchmaker) for discovering web services that are available intermittently is presented based on the concept of agent roles; (2) A selection algorithm based on risk-enabled reputation model (REAL) embedded in a manager agent (as a service composer) is introduced to serve a basis for selecting web services with variant performance; and (3) A negotiation mechanism between a manager agent and contractor agents (as atomic services) is devised and enables both a service composer and the atomic services to request, refuse or agree on adapting changes of services.ResultsThe problem of assembling a computer is discussed in this paper.ConclusionIt is increasingly recognised that web services would become more autonomous by introducing diverse agent technologies to better constitute more complex systems in open and dynamic environments. As web service technologies are best exploited by composite services, it is imperative to devise mechanisms for composing services of autonomy.     

THE STROBE MODEL: DYNAMIC SERVICE GENERATION ON THE GRID

This article presents the STROBE model: both an agent representation and an agent communication, model based on a social approach, which means interaction centered. This model represents how agents may realize the interactive, dynamic generation of services on the Grid. Dynamically generated services embody a new concept of service implying a collaborative creation of knowledge, i.e., learning; services are constructed interactively between agents depending on a conversation. The approach consists of integrating selected features from multi-agent systems and agent communication, language interpretation in applicative/functional programming and e-learning/human-learning into a unique, original, and simple view that privileges interactions, including control. The main characteristic of STROBE agents is that they develop a language (environment + interpreter) for each of their interlocutors. The model is inscribed within a global approach, defending a shift from the classical algorithmic (control based) view to problem solving in computing to an interaction-based view of social informatics, where artificial as well as human agents operate by communicating as well as by computing. The paper shows how the model may not only account for the classical communicating agent approaches, but also represent a fundamental advance in modeling societies of agents in particular in dynamic service generation scenarios such as those necessary today on the Web and proposed tomorrow for the Grid. Preliminary concrete experimentations illustrate the potential of the model; they are significant examples for a very wide class of computational and learning situations.     

Semantic segmentation of trajectories with improved agent models for pedestrian behavior analysis

ABSTRACT

In this paper, we propose a method for semantic segmentation of pedestrian trajectories based on pedestrian behavior models, or agents. The agents model the dynamics of pedestrian movements in two-dimensional space using a linear dynamics model and common start and goal locations of trajectories. First, agent models are estimated from the trajectories obtained from image sequences. Our method is built on top of the Mixture model of Dynamic pedestrian Agents (MDA); however, the MDA's trajectory modeling and estimation are improved. Then, the trajectories are divided into semantically meaningful segments. The subsegments of a trajectory are modeled by applying a hidden Markov model using the estimated agent models. Experimental results with a real trajectory dataset show the effectiveness of the proposed method as compared to the well-known classical Ramer-Douglas-Peucker algorithm and also to the original MDA model.     

Interfacing Indigolog and OAA: A Toolkit for Advanced Multiagent Applications

In this paper, we describe an interface library IG-OAAlib that supports the development of Open Agent Architecture (OAA) agents using the INDIGOLOG agent programming language. OAA is a multi-agent infrastructure that supports facilitated communication. INDIGOLOG is a high-level agent programming language based on logic that supports planning and allows complex agent behaviors to be specified. Full-fledged INDIGOLOG agents written using our interface library can be both reactive and proactive, thus overcoming one of the limitations of PROLOG-based agents in the OAA framework. The interface hides all of the low-level procedures that are used to communicate with the OAA system, as well as OAA initialization, thereby leaving the INDIGOLOG programmer free to concentrate on the functionality of the agent. A multi-robot mail delivery application developed using the library is presented.     

Vivid agents: Theory,architecture, and applications

Vivid agents (Wagner, 1996) are software-controlled systems whose state comprises the mental components of knowledge, perceptions, tasks, and intentions, and whose behavior is represented by means of action and reaction rules. An execution model for vivid agents is presented, which is based on an architecture for concurrent action and planning (CAP). The concept of vivid agents and the CAP architecture in distributed diagnosis is evaluated, including fault-tolerant diagnosis and the diagnosis of an unreliable communication protocol.     

Heterogeneous Agents Situated in Heterogeneous Spaces

This paper introduces the Multi-layered Multi-Agent Situated System model (MMASS), a model for Multi-Agent Systems (MAS) situated in an environment. The main feature of the MMASS model is to give an explicit definition of the spatial structure of the environment in which the system of situated agents are acting and interacting. Moreover, the presented model allows the representation of the heterogeneity that characterizes both agent types and interactions, and the spatial structures of the environment in which they are situated. The MMASS model allows the representaton of both open and closed systems: examples of its application (one for each class of systems) will be shown.     

MULTI-AGENT INFRASTRUCTURES FOR OBJECTIVE AND SUBJECTIVE COORDINATION

Coordination in multi-agented systems (MAS) can be conceived as either an agent activity (the subjective viewpoint) or an activity over agents (the objective viewpoint). The two viewpoints have generated two diverging and often contrasting lines of research, as well as different and noncompatible technologies, however, their integration is mandatory for modeling and engineering complex MAS. In this paper, we explore the issue of integration at both the model and the technology levels.

First, by taking FIPA agents and coordination artifacts as reference notions for subjective and objective approaches, respectively, we sketch a framework where agent interactions with coordination artifacts are modeled as physical acts, deliberated and executed by agents analogously to communicative actions. Then, we show how the JADE infrastructure for FIPA-compliant agents, and the TuCSoN infrastructure providing agents with coordination artifacts can be integrated at the technology level, allowing JADE agents to access TuCSoN tuple centers through JADE services.     

Can a rational agent afford to be affectless? a formal approach

In this article, we expose some of the issues raised by the critics of the neoclassical approach to rational agent modeling and we propose a formal approach for the design of artificial rational agents that includes some of the functions of emotions found in the human system. We suggest that emotions and rationality are closely linked in the human mind (and in the body, for that matter) and, therefore, need to be included in architectures for designing rational artificial agents, whether these agents are to interact with humans, to model humans' behaviors and actions, or both. We describe an Affective Knowledge Representation (AKR) scheme to represent emotion schemata, which we developed to guide the design of a variety of socially intelligent artificial agents. Our approach focuses on the notion of "social expertise" of socially intelligent agents in terms of their external behavior and internal motivational goal-based abilities. AKR, which uses probabilistic frames, is derived from combining multiple emotion theories into a hierarchical model of affective phenomena useful for artificial agent design. AKR includes a taxonomy of affect, mood, emotion, and personality, and a framework for emotional state dynamics using probabilistic Markov Models.     

Abc classification with uncertain data. a fuzzy model vs. a probabilistic model

This study presents an alternative way of classifying the different productive items of a company. A fuzzy model for the magnitudes involved (demand and cost) is described. This model contrasts with the classic Pareto classification (ABC), which ranks productive items according to their importance in terms of frequency and costs. Whereas rankings obtained using the classical method are based on information about costs and demand over a period in the past, this new method allows new fuzzy information about the future to be included, thus allowing stricter control of the fuzzy ''A-items'' that result from this new classification. Rankings comparing a probabilistic model and its fuzzy counterpart are also provided in this study.     

Using bayesian networks to model agent relationships

An agent-society of the future is envisioned to be as complex as a human society. Just like human societies, such multiagent systems (MAS) deserve an in-depth study of the dynamics, relationships, and interactions of the constituent agents. An agent in a MAS may have only approximate a priori estimates of the trustworthiness of another agent. But it can learn from interactions with other agents, resulting in more accurate models of these agents and their dependencies together with the influences of other environmental factors. Such models are proposed to be represented as Bayesian or belief networks. An objective mechanism is presented to enable an agent elicit crucial information from the environment regarding the true nature of the other agents. This mechanism allows the modeling agent to choose actions that will produce guaranteed minimal improvement of the model accuracy. The working of the proposed maxim in entropy procedure is demonstrated in a multiagent scenario.     

Mind model for multimodal communicative creatures and humanoids

This paper presents a computational model of real - time task - oriented dialog skills . The model , termed Ymir, bridges multimodal perception and multimodal action and supports the creation of autonomous computer characters that afford full - duplex , real - time face - to - face interaction with a human . Ymir has been prototyped in software , and a humanoid created , called Gandalf, capable of fluid multimodal dialog . Ymir demonstrates several new ideas in the creation of communicative computer agents , including perceptual integration of multimodal events, distributed planning and decision making, an explicit handling of real time, and perceptuo-motor system layered and motor control with human characteristics. This paper describes the model's architecture and explains its main elements . Examples of implementation and performance are given , and the architecture's limitations and possibilities are discussed .     

Agent-based approach for manufacturing integration: The ciimplex experience

The production management system used by most manufacturers today consists of disconnected planning and execution processes and lacks the support for interoperability and collaboration needed for enterprise-wide integration. This situation often prevents the manufacturer from fully exploring market opportunities in a timely fashion. To address this problem, we are exploring an agent-based approach to intelligent enterprise integration. In this approach, a set of agents with specialized expertise can be quickly assembled to help with the gathering of relevant information and knowledge, to cooperate with each other and with other parts of the production management system and humans to arrive at timely decisions in dealing with various enterprise scenarios. The proposed multiagent system, including its architecture and implementation, is presented and demonstrated through an example integration scenario involving real planning and execution software systems.     

Parabolic PDE-based multi-agent formation control on a cylindrical surface

ABSTRACT

This paper considers the modelling and control design of the multi-agent systems in the 3-D space. The communication graph of the agents is a mesh-grid 2-D cylindrical surface. Different from most existing literatures, where the agents are modelled by ordinary differential equations (ODEs), we treat the agents as a continuum in this paper. More specifically, we model the collective dynamics of the agents by two reaction–advection–diffusion 2-D partial differential equations (PDEs). The PDE states represent the agent positions, and the equilibria correspond to possible formation manifolds. These PDEs can be open-loop unstable, and the boundary stabilisation problem of the PDEs on the cylindrical surface is solved using the backstepping method. An all-explicit observer-based output control scheme is constructed, which is distributed in the sense that each agent only needs local information. Closed-loop exponential stability in the L ², H ¹, and H ² spaces is proved for the controller designs. Numerical simulations illustrate the effectiveness of our proposed approach.