MultiAgent Systems

MultiAgent Systems

• Distributed Artificial Intelligence

• MultiAgent Systems

• Characteristics of MAS

• Challenges of MAS

• Networking

• Remote Method Invocation

• Uniform Resource Location

Distributed Problem Solving

• How a particular problem can be solved by a number of modules, which cooperate in dividing and sharing knowledge about the problem and its evolving solutions.

• All iteraction strategies are incoporated as an integral part of the system.

Distributed Problem Solving

MultiAgent Systems

• Concerned with the behavior of a collection of possibly pre-existing autonomous agents aiming at solving a given problem.

• a loosely coupled network of problem solvers that work together to solve problems that are beyond the individual capabilities or knowledge of each problem solver

MultiAgent Systems

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Characteristics

• each agent has incomplete information, or capabilities for solving the problem, thus each agent has a limited viewpoint

• there is no global system control;

• data is decentralized; and

• computation is asynchronous.

Why MAS?

• the ability to provide robustness and efficiency;

• the ability to allow inter-operation of existing legacy systems; and

• the ability to solve problems in which data, expertise, or control is distributed.

Challenges

• How to formulate, describe, decompose, and allocate problems and synthesize results among a group of intelligent agents?

• How to enable agents to communicate and interact? What communication languages and protocols to use? What and when to communicate?

Challenges

• How to ensure that agents act coherently in making decisions or taking action, accommodating the non-local effects of local decisions and avoiding harmful interactions?

• How to enable individual agents to represent and reason about the actions, plans, and knowledge of other agents in order to coordinate with them? How to reason about the state of their coordinated process (e.g., initiation and completion)?

Challenges

• How to recognize and reconcile disparate viewpoints and conflicting intentions among a collection of agents trying to coordinate their actions?

• How to effectively balance local computation and communication? More generally, how to manage allocation of limited resources?

Challenges

• How to avoid or mitigate harmful overall system behavior, such as chaotic or oscillatory behavior?

• How to engineer and constrain practical MAS systems? How to design technology platforms and development methodologies for MAS?

Networking

• Open System Interconnection

• Socket– IP Address– Port

• ServerSocket

• RMI

• URL

OSI Model

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Socket

• ConstructionSocket s = new Socket(hostName, port);• Read from SocketBufferedReader r = new BufferedReader( new InputSreamReader(s.getInputStream());• Write to SocketPrintWriter o = new PrintWriter( s.getOutpuStream(), true);o.println(”message”);

ServerSocket

C lie nt Se rve r

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ServerSocket

• ServerSocket server = new

ServerSocket(port);

while (true) {

Socket client = server.accept();

< handle the client>

}

Remote Method Invocation

Remote

RMIClientRMIServer

<<Interface>>

RMIServerImpl

RMI

• Rmiregistry finds registry-name• Server:

Registry r = LocateRegistry.getRegistry();

r.rebind(Registry_Name, server);• Client:

Registry reg = LocateRegistry().getRegistry();

server = (RMIServer) reg.lookup(Registry_Name);

URL

• Make a URL

URL s = new URL(”http://...”);

• Read the source– Get object content: Object o = s.getContent();– Convert o to InputStream: is = (InputStram)o;– Read each line from BufferedReader

URL

• Display a URL– LinkListener:Class LinkListener implements HyperlinkListener{ public void hyperlinkUpdate(HyperlinkEvent e) { if (e.getEventType() == HyperlinkEvent.EventType.ACTIVATED)

showPage(e.getURL).toString()); }}– showPageJEditorPane content;void showPage(String location) {

try {content.setPage(location);

} catch() {}}