Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Agents in a team must be in agreement. Unfortunately, they may come to disagree due to sensing uncertainty, communication failures, etc. Once a disagreement occurs  should detect the disagreement and diagnose it. Unfortunately, current diagnosis techniques do not scale ll with the number of agents, as they have high communication and computation complexity.  suggest three techniques to reduce this complexity: (i) reducing the amount of diagnostic reasoning by sending targeted queries; (ii) using light-ight behavior recognition to recognize which beliefs of the agents might be in conflict; and (iii) grouping the agents according to their role and behavior and then diagnosing the groups based on representative agents.  examine these techniques in large-scale teams, in two domains, and show that combining the techniques produces a diagnosis process which is highly scalable in both communication and computation.
['Meir Kalech', 'Gal A. Kaminka']
I am writing a research paper on a idea Diagnosing a Team of Agents: Scaling-Up
[{"from": "human", "value": "I am writing a research paper on a idea Diagnosing a Team of Agents: Scaling-Up"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Agents in a team must be in agreement. Unfortunately, they may come to disagree due to sensing uncertainty, communication failures, etc. Once a disagreement occurs  should detect the disagreement and diagnose it. Unfortunately, current diagnosis techniques do not scale ll with the number of agents, as they have high communication and computation complexity.  suggest three techniques to reduce this complexity: (i) reducing the amount of diagnostic reasoning by sending targeted queries; (ii) using light-ight behavior recognition to recognize which beliefs of the agents might be in conflict; and (iii) grouping the agents according to their role and behavior and then diagnosing the groups based on representative agents.  examine these techniques in large-scale teams, in two domains, and show that combining the techniques produces a diagnosis process which is highly scalable in both communication and computation."}]