Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  explore approximate policy iteration, replacing the usual cost-function learning step with a learning step in policy space.  give policy-language biases that enable solution of very large relational Markov decision processes (MDPs) that no previous technique can solve. In particular,  induce high-quality domain-specific planners for classical planning domains (both deterministic and stochastic variants) by solving such domains as extremely large MDPs.
['Alan Fern', 'Sung Wook Yoon', 'Robert Givan']
I am writing a research paper on a idea Approximate Policy Iteration with a Policy Language Bias
[{"from": "human", "value": "I am writing a research paper on a idea Approximate Policy Iteration with a Policy Language Bias"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  explore approximate policy iteration, replacing the usual cost-function learning step with a learning step in policy space.  give policy-language biases that enable solution of very large relational Markov decision processes (MDPs) that no previous technique can solve. In particular,  induce high-quality domain-specific planners for classical planning domains (both deterministic and stochastic variants) by solving such domains as extremely large MDPs."}]