Agent Technology from a Formal Perspective : Christopher A. Rouff :
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Agent Technology from a Formal Perspective During the last several years the? Meanwhile the?
Thus in it was quite timely to pursue a workshop to merge the concerns of the two? The need for such a workshop was particularly compelling given the growing concerns of agent-basedsystemsusersthattheirsystemsshouldbeaccompaniedby behavioral assurances. This book is organized into four parts. Part I provides introductory backgroundmaterialonthetwocentraltopicsofthebooknamelyagents andformalmethods. Thechapter- gins by introducing the basic concept of an agent from a very simple abstractperspective.
First the major architectural components e. Then agent behaviors are de? Thechapterconcludeswithan intriguingdiscussionofmulti-agentcommunities. Email Address. Sign In. Access provided by: anon Sign Out. Formal describing the organizations in the pervasive healthcare information system: Multi-agent system perspective Abstract: With the development of computing technology, the architecture of healthcare information systems HIS may evolve into an application of pervasive computing.
HIS requires a more complex high-level design because of its involvement of many different organizations with individual interests and goals. Therefore, an agent-oriented architecture is preferable over other traditional models, such as object-oriented and service-oriented architectures. Bowen, and Christopher A. Rouff, James L. Rash, Michael G. Hinchey, and Walter F. Truszkowski 1.
Teamwork in MultiAgent Systems: A Formal Approach (Wiley Series in Agent Technology)
A few comments about agent communities ensues. We then proceed by considering a complete agent architecture and begin to look at the individual pieces components that compose it. This architecture was developed by the agent-group at the Goddard Space Flight Center as a centerpiece for some of its initial research in applied agent technology. The application domain was ground-based and spacebased satellite operations. Consider Figure 1. Environmenti Perceptsi - Actionsi Agenti - Fig.
Agent Technology from a Formal Perspective (NASA Monographs in Systems and Software Engineering)
Abstract view of an agent. An agent exists in an environment and, in some cases, may itself be considered to be a contributing part of the environment. Agent - Sensors - Processes - Effectors - Fig. Basic structure of an agent. Sensors may be considered to be environmental probes. The spectrum of possible degrees of intelligence for agents is quite broad.
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An agent may act in a stimulus-response mode, automatically performing some activity. This is the type of behavior normally associated with simple expert systems that may be considered as simple agents. Other levels of processing may require more deliberation. The Goddard agent architecture is a highly component-based modular architecture. Components, when combined with other software components, can constitute a more robust piece of software that is easily maintained and upgraded.
Components interact with one another through various communication mechanisms. Components may be implemented with a degree of intelligence through the addition of, for example, reasoning and learning functions. The use of components is intended to facilitate maintaining and upgrading agent systems.
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A component needs to implement certain interfaces and embody certain properties. In our case, components must implement functionality to publish information and subscribe to information, and must be able to accept queries for information from other components or objects. In order to function properly, components need to keep a status of their state, 6 Agent Technology from a Formal Perspective know what types of information they possess, and know what types of information they need from external components and objects.
Components can communicate through different mechanisms. A simple agent can be designed using a minimum number of simple components that would receive percepts from the environment and react to those percepts. A robust agent may be designed to use many components that allow the agent to do what a simple agent does and, in addition, reason, plan, schedule, model the environment, and learn.
The following architecture Figure 1. These components give the agent a higher degree of intelligence when interacting with its environment, i. Environment 6? Agent Reasoning Goals? A robust agent with planning, modeling, and reasoning capabilities. The Agent Reasoning component reasons with respect to received ACL messages, knowledge that it contains, and information that is acquired from the Modeling and State component to formulate goals for the agent when necessary.
Goals are then acquired by the Planning component along with state and state transition information. The Planning component formulates a plan for the agent to achieve the desired goals. Steps are marked when they are ready for execution and the completion status of each step is also tracked by the Agenda. State changes will be recorded by the Modeling and State component. The architecture under discussion incorporates a distributed knowledge-base. Each component that creates or stores a kind of information is responsible for keeping that information current.
Distributing responsibility for knowledge is advantageous when compared to a central, shared knowledge-base. With a central, shared knowledge-base, the knowledgebase component needs to understand the content of all data it keeps in order to allow it to update data appropriately and keep data current. In the architecture under discussion, the Modeling and State component is the closest thing to a centralized knowledge base for the agent.
What follows is a closer look at each component in the agent architecture. The agent may receive percepts from systems, the operating environment, or sensors and, in turn, affect systems 8 Agent Technology from a Formal Perspective or the operating environment. The agent may also communicate with other agents located in its Environment. In the above-described overall architecture, any data received by the agent from the environment, other than agent-to-agent messages, enters through Perceptors.
A purely social agent see Sections 3. A Perceptor may also act intelligently through the use of reasoning systems if it is desired. The end of this section gives examples. Environment Data? Percepts Translator Perceptor Fig. Agent perceptor component. The spacecraft, in this event, is the environment for the agent.
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This information can then be used by the Modeling and State component to update its models and knowledge bases see section 2.
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