Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The scalability of an evolved multi-agent system is an important characteristic of the system. The multi-agent system is normally evolved in a particular configuration of system parameters. Hover, an optimized solution using one set of system parameters does not necessarily means a good solution using a different set of system parameters. The research presented in this paper studies the performance scalability of evolved solutions in reactive multi-agent systems for the heap formation task. The scalability variable considered in the research was the cardinality of the agents group, whereas keeping the rest of the system and collective resources invariable. In the first phase of the experiments, best solutions for different system configurations re found using genetic algorithm. In the second phase, the evolved solutions re cross-tested in all system configurations. The research shod that evolved solutions performed ll if the agents/objects ratio of the multi-agent system used in testing was similar to the agents/objects ratio of the multi-agent system used in evolution. Additionally, evolved solutions scaled ll only on limited intervals that did not span over the critical point, which corresponded to the condition where the number of agents is equal to the number of objects. Typically, solutions that performed ll on one side of the critical point performed badly on the other side, suggesting the solutions performances re significantly dependant on agents/objects ratio.
['Marko Privosnik']
I am writing a research paper on a idea The scalability of evolved on line bin packing heuristics
[{"from": "human", "value": "I am writing a research paper on a idea The scalability of evolved on line bin packing heuristics"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The scalability of an evolved multi-agent system is an important characteristic of the system. The multi-agent system is normally evolved in a particular configuration of system parameters. Hover, an optimized solution using one set of system parameters does not necessarily means a good solution using a different set of system parameters. The research presented in this paper studies the performance scalability of evolved solutions in reactive multi-agent systems for the heap formation task. The scalability variable considered in the research was the cardinality of the agents group, whereas keeping the rest of the system and collective resources invariable. In the first phase of the experiments, best solutions for different system configurations re found using genetic algorithm. In the second phase, the evolved solutions re cross-tested in all system configurations. The research shod that evolved solutions performed ll if the agents/objects ratio of the multi-agent system used in testing was similar to the agents/objects ratio of the multi-agent system used in evolution. Additionally, evolved solutions scaled ll only on limited intervals that did not span over the critical point, which corresponded to the condition where the number of agents is equal to the number of objects. Typically, solutions that performed ll on one side of the critical point performed badly on the other side, suggesting the solutions performances re significantly dependant on agents/objects ratio."}]