Explain Communication among agents in Artificial Intelligence
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Agents in a multi-agent system can communicate and cooperate to solve problems. They communicate through various methods like point-to-point, broadcast, or mediated communication to coordinate actions and share information. Common communication approaches include blackboard-based communication where agents access a shared information space, and message passing where agents directly exchange varied information to facilitate cooperation.
Explain Communication among agents in Artificial Intelligence
- 1. Visit: http://gsbprogramming.blogspot.in _____________________________________________________________________________________________________________________ Q: Explain Communication among agents. Ans: What is a Multi-Agent System? A multi-agent system(MAS) may be seen as a collection of collaborative agents They can communicate and cooperate with other agents, while keeping their autonomy They usually negotiate with their peers to reach mutually acceptable agreements during cooperative problem solving Collaborative agents normally have limited learning capabilities Collaborative agents are usually deliberative agents (e.g. BDI model), with some reasoning capabilities Reactive agents can hardly communicate and collaborate (only through actions that modify the common environment). They are usually static, complex agents Benefits of Multi Agent System: 1. Modularity Each agent is specialized in the solution of a particular kind of problems (leading also to reusability) The complexity of the construction of agents is reduced The process of solving a complex problem is reduced to solving easier sub problems 2. Efficiency
- 2. Visit: http://gsbprogramming.blogspot.in _____________________________________________________________________________________________________________________ Problems can be solved more quickly, due to the inherent concurrency/parallelism Different agents are working at the same time in different parts of a problem 3. Reliability Avoid single point of failure in centralized systems If an individual agent fails, the other agents can take its work and re- distribute it dynamically 4. Flexibility Agents can be created/deleted dynamically, depending on the amount of work to be done, the available resources, etc. Agents can dynamically generate subtasks and look for helping agents Why do we need Agent Communication? Multi agent systems allow distributed problem solving This requires the agents to coordinate their actions Agent communication facilitates this by allowing individual agents to interact -allow cooperation -allow information sharing Communication can be: Point to Point- An agent talks directly to another agent
- 3. Visit: http://gsbprogramming.blogspot.in _____________________________________________________________________________________________________________________ Broadcast- An agent sends some information to a group of agents Mediated- The communication between two agents is mediated by a third party. Example: Facilitators
- 4. Visit: http://gsbprogramming.blogspot.in _____________________________________________________________________________________________________________________ Agent Communication 1. BlackBoard Based Communication:
- 5. Visit: http://gsbprogramming.blogspot.in _____________________________________________________________________________________________________________________ Each agent can put information/data/knowledge on the common information space Each agent can read from the blackboard at any moment There is no direct communication between agents
- 6. Visit: http://gsbprogramming.blogspot.in _____________________________________________________________________________________________________________________ 2. Message Passing Information is passed from one agent to another. The nature of this information can be very varied. Speech acts provide one way to describe this variety.