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Cooperation Control of a Set of Robots with Different Expertise to Accomplish a Duty

Mortazi, Ali Asghar | 2014

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 46415 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Bagheri Shouraki, Saeed
  7. Abstract:
  8. In recent years, there have been many efforts for distributing a big and complex duty among some agents in order to do it more simply. Large number of these methods are in area called distributed systems, where several different agents start to work together to do a difficult or complex duty which each of them cannot do it lonely. Combination of distributed systems and artificial intelligence is known as distributed artificial intelligence.
    One of the theories that has received attention recently, is called Embodiment. According this theory, in cooperation of a set of agents for performing particular task, expertise might not be integrated in a centralized controller, rather it gradually spreads to component and agents of task. Based on this theory, despite the fact that the human brain is the main controller, expertise is integrated in the body organs gradually. In multi agent system a central controller controls and programs whole duties and jobs that agents should perform, this leads to have a very complicated central controller. While in embodiment systems, initially each robot separately, with different structures, are fed with some knowledge in the specific duty and then placed together to accomplish a common task.
    Now, we will examine this issue that how much improvement is earned when every agent has got a specific amount of partial knowledge separately in comparison with whole structure is defined beforehand. We try to implement embodied system on legs of a quadruped and compare result with the multi agent system
  9. Keywords:
  10. Artificial Intelligence ; Distributed Artificial Intelligence (DAI) ; Multiagent System ; Distributed System ; Embodiment Approach

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