Situation Assessment for Plan Retrieval

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Kyran
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Situation Assessment for Plan Retrieval

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A paper by Kinshuk Mishra, Santiago Ontanon, and Ashwin Ram.
Case-Based Planning (CBP) is an effective technique for solving planning problems that has the potential to reduce the computational complexity of the generative planning approaches. However, the success of plan execution using CBP depends highly on the selection of a correct plan; especially when the case-base of plans is extensive. In this paper we introduce the concept of a situation and explain a situation assessment algorithm which improves plan retrieval for CBP. We have applied situation assessment to our previous CBP system, Darmok, in the domain of real-time strategy games. During Darmok’s execution using situation assessment, the high-level representation of the game state i.e. situation is predicted using a decision tree based Situation Classification model. Situation predicted is further used for the selection of relevant knowledge intensive features, which are derived from the basic representation of the game state, to compute the similarity of cases with the current problem. The feature selection performed here is knowledge based and improves the performance of similarity measurements during plan retrieval. The instantiation of the situation assessment algorithm to Darmok gave us promising results for plan retrieval within the real-time constraints.
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04:27 jim4 why haven't you added wc1 support? this project sucks. i'm only going to use freecraft
05:06 jim4 finished wc1 support yet? i've been waiting for 6 years
05:10 jim4 new things scare me
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