Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce Distributed perception networks (DPNs), a distributed architecture for efficient and reliable fusion of large quantities of heterogeneous and noisy information. DPNs consist of agents, processing nodes with limited fusion capabilities, which cooperate and can autonomously form arbitrarily large distributed classifiers. DPNs are based on causal models, which often facilitate analysis, design and maintenance of complex information fusion systems. This is possible because observations obtained from different information sources often result from causal processes which in turn can be modeled with relatively simple, yet mathematically rigorous and compact probabilistic causal models. Such models, in turn, facilitate decentralized world modeling and information fusion.
['Gregor Pavlin', 'P. de Oude', 'Marinus Maris']
I am writing a research paper on a idea Distributed Perception Networks: An Architecture for Information Fusion Systems Based on Causal Probabilistic Models
[{"from": "human", "value": "I am writing a research paper on a idea Distributed Perception Networks: An Architecture for Information Fusion Systems Based on Causal Probabilistic Models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce Distributed perception networks (DPNs), a distributed architecture for efficient and reliable fusion of large quantities of heterogeneous and noisy information. DPNs consist of agents, processing nodes with limited fusion capabilities, which cooperate and can autonomously form arbitrarily large distributed classifiers. DPNs are based on causal models, which often facilitate analysis, design and maintenance of complex information fusion systems. This is possible because observations obtained from different information sources often result from causal processes which in turn can be modeled with relatively simple, yet mathematically rigorous and compact probabilistic causal models. Such models, in turn, facilitate decentralized world modeling and information fusion."}]