Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The exponential growth of the size of the search space has always been an obstacle to POMDP planning. Heuristics are often used to reduce the search space size and improve computational efficiency. As the advantage of the feature of POMDP problems should be taken into deeper consideration,  analyze the clustering feature of reachable space of POMDP problems and apply policy iteration based on this clustering feature. With insights from theoretical analysis,  have developed a practical POMDP algorithm Point Clustering Feature Based Policy Iteration (PCFBPI). Empirically, PCFBPI is competitive with PBPI in terms of solution quality and convergence efficiency on some large-scale problems.
['Feng Liu', 'Chongjun Wang', 'Jidong Ge', 'Bin Luo']
I am writing a research paper on a idea PCFBPI: A Point Clustering Feature Based Policy Iteration Algorithm
[{"from": "human", "value": "I am writing a research paper on a idea PCFBPI: A Point Clustering Feature Based Policy Iteration Algorithm"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The exponential growth of the size of the search space has always been an obstacle to POMDP planning. Heuristics are often used to reduce the search space size and improve computational efficiency. As the advantage of the feature of POMDP problems should be taken into deeper consideration,  analyze the clustering feature of reachable space of POMDP problems and apply policy iteration based on this clustering feature. With insights from theoretical analysis,  have developed a practical POMDP algorithm Point Clustering Feature Based Policy Iteration (PCFBPI). Empirically, PCFBPI is competitive with PBPI in terms of solution quality and convergence efficiency on some large-scale problems."}]