Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new problem-solving approach, termed simulation-based policy generation (SPG), that is able to generate solutions to problems that may otherwise be computationally intractable. The SPG method uses a simulation of the original problem to create an approximating Markov decision process (MDP) model which is then solved via traditional MDP solution approaches. Since this approximating MDP is a fairly rich and robust sequential optimization model, solution policies can be created which represent an intelligent and structured search of the policy space. An important feature of the SPG approach is its adaptive nature, in that it uses the original simulation model to generate improved aggregation schemes, allowing the approach to be applied in situations where the underlying problem structure is largely unknown. In order to illustrate the performance of the SPG methodology,  apply it to a common but computationally complex problem of inventory control, and  briefly discuss its application to a large-scale telephone network routing problem.
['Christopher W. Zobel', 'William T. Scherer']
I am writing a research paper on a idea Simulation-based policy generation using large-scale Markov decision processes
[{"from": "human", "value": "I am writing a research paper on a idea Simulation-based policy generation using large-scale Markov decision processes"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new problem-solving approach, termed simulation-based policy generation (SPG), that is able to generate solutions to problems that may otherwise be computationally intractable. The SPG method uses a simulation of the original problem to create an approximating Markov decision process (MDP) model which is then solved via traditional MDP solution approaches. Since this approximating MDP is a fairly rich and robust sequential optimization model, solution policies can be created which represent an intelligent and structured search of the policy space. An important feature of the SPG approach is its adaptive nature, in that it uses the original simulation model to generate improved aggregation schemes, allowing the approach to be applied in situations where the underlying problem structure is largely unknown. In order to illustrate the performance of the SPG methodology,  apply it to a common but computationally complex problem of inventory control, and  briefly discuss its application to a large-scale telephone network routing problem."}]