{"title":"强规划算法的改进","authors":"Zhonghua Wen, Qiwei Yang, Jinhua Zheng, Jiang Zhu","doi":"10.1109/ICNC.2008.723","DOIUrl":null,"url":null,"abstract":"This paper points out some drawbacks and gives some modifications to the strong planning algorithm. In particular, a set of states is found by using of adjacency matrix that corresponds to a non-deterministic state-transition system. The set of states is composed of four parts, the first part is a part of initial states which can not reach goal states, if the first part is not empty, there is not strong planning; if a state which is not a initial state can not reach goal states,we put the state into the second part; the third part are the states that are unreachable from the initial states; so the station-action pairs which relate to the second part or third part are absolutely useless; the fourth part are the states which the initial states can not reach without passing any goal state before, the state-action pairs which relate to the fourth part are useless as well, because they move the execution away from the goal. So a great many of state-action pairs can be eliminated directly from the universal policy. Finally, the efficiency of the modified algorithm is illustrated by an example and some experiments.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"85 1","pages":"506-510"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improvements to the Strong Planning Algorithm\",\"authors\":\"Zhonghua Wen, Qiwei Yang, Jinhua Zheng, Jiang Zhu\",\"doi\":\"10.1109/ICNC.2008.723\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper points out some drawbacks and gives some modifications to the strong planning algorithm. In particular, a set of states is found by using of adjacency matrix that corresponds to a non-deterministic state-transition system. The set of states is composed of four parts, the first part is a part of initial states which can not reach goal states, if the first part is not empty, there is not strong planning; if a state which is not a initial state can not reach goal states,we put the state into the second part; the third part are the states that are unreachable from the initial states; so the station-action pairs which relate to the second part or third part are absolutely useless; the fourth part are the states which the initial states can not reach without passing any goal state before, the state-action pairs which relate to the fourth part are useless as well, because they move the execution away from the goal. So a great many of state-action pairs can be eliminated directly from the universal policy. Finally, the efficiency of the modified algorithm is illustrated by an example and some experiments.\",\"PeriodicalId\":6404,\"journal\":{\"name\":\"2008 Fourth International Conference on Natural Computation\",\"volume\":\"85 1\",\"pages\":\"506-510\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Fourth International Conference on Natural Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2008.723\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Fourth International Conference on Natural Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2008.723","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper points out some drawbacks and gives some modifications to the strong planning algorithm. In particular, a set of states is found by using of adjacency matrix that corresponds to a non-deterministic state-transition system. The set of states is composed of four parts, the first part is a part of initial states which can not reach goal states, if the first part is not empty, there is not strong planning; if a state which is not a initial state can not reach goal states,we put the state into the second part; the third part are the states that are unreachable from the initial states; so the station-action pairs which relate to the second part or third part are absolutely useless; the fourth part are the states which the initial states can not reach without passing any goal state before, the state-action pairs which relate to the fourth part are useless as well, because they move the execution away from the goal. So a great many of state-action pairs can be eliminated directly from the universal policy. Finally, the efficiency of the modified algorithm is illustrated by an example and some experiments.