α-MCMP: Trade-Offs Between Probability and Cost in SSPs with the MCMP Criterion.
BRACIS (1)(2023)
摘要
In Stochastic Shortest Path (SSP) problems, not always the requirement of having at least one policy with a probability of reaching goals (probability-to-goal) equal to 1 can be met. This is the case when dead ends, states from which the probability-to-goal is equal to 0, are unavoidable for any policy, which demands the definition of alternate methods to handle such cases. The α -strong probability-to-goal priority is a property that is maintained by a criterion if a necessary condition to optimality is that the ratio between the probability-to-goal values of the optimal policy and any other policy is bound by a value of 0 ≤ α ≤ 1 . This definition is helpful when evaluating the preference of different criteria for SSPs with dead ends. The Min-Cost given Max-Prob (MCMP) criterion is a method that prefers policies that minimize a well-defined cost function in the presence of unavoidable dead ends given policies that maximize probability-to-goal. However, it only guarantees α -strong priority for α = 1 . In this paper, we define α -MCMP, a criterion based on MCMP with the addition of the guarantee of α -strong priority for any value 0 ≤ α ≤ 1 . We also perform experiments comparing α -MCMP and GUBS, the only other criteria known to have α -strong priority for 0 ≤ α ≤ 1 , to analyze the difference between the probability-to-goal of policies generated by each criterion.
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关键词
$$-mcmp criterion,ssps,cost,$$\alpha,trade-offs
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