Matches in SemOpenAlex for { <https://semopenalex.org/work/W2024605041> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W2024605041 abstract "This paper presents a reinforcement learning (RL) algorithm for multi-agent patrol tasks, which can be thought of as a dynamic programming problem with stochastic demands. We define the cover rate as the reward, the multi-agent physical positions including edges and nodes as the state, and the nodes adjacent to the agent as the action to model the patrol task. The modeling of this problem is totally different from other's work, which facilitates the communication and cooperation among these agents. Furthermore, we map the state from four dimensions to one dimension in order to improve the training efficiency and reduce the coding complexity. A deterministic Softmax algorithm is designed for comparison. We test both two algorithms in patrolling and rescuing scenarios. Results show the patrol cover rate with RL greatly outperforms Softmax about 15.38%, and the average rescue time for emergent pots is reduced by 20% with RL compared to Softmax." @default.
- W2024605041 created "2016-06-24" @default.
- W2024605041 creator A5012412127 @default.
- W2024605041 creator A5050937164 @default.
- W2024605041 date "2010-07-01" @default.
- W2024605041 modified "2023-09-27" @default.
- W2024605041 title "Reinforcement learning for multi-agent patrol policy" @default.
- W2024605041 cites W2007572995 @default.
- W2024605041 cites W2108950458 @default.
- W2024605041 doi "https://doi.org/10.1109/coginf.2010.5599681" @default.
- W2024605041 hasPublicationYear "2010" @default.
- W2024605041 type Work @default.
- W2024605041 sameAs 2024605041 @default.
- W2024605041 citedByCount "9" @default.
- W2024605041 countsByYear W20246050412012 @default.
- W2024605041 countsByYear W20246050412013 @default.
- W2024605041 countsByYear W20246050412016 @default.
- W2024605041 countsByYear W20246050412018 @default.
- W2024605041 countsByYear W20246050412019 @default.
- W2024605041 countsByYear W20246050412022 @default.
- W2024605041 countsByYear W20246050412023 @default.
- W2024605041 crossrefType "proceedings-article" @default.
- W2024605041 hasAuthorship W2024605041A5012412127 @default.
- W2024605041 hasAuthorship W2024605041A5050937164 @default.
- W2024605041 hasConcept C105795698 @default.
- W2024605041 hasConcept C110698143 @default.
- W2024605041 hasConcept C127413603 @default.
- W2024605041 hasConcept C154945302 @default.
- W2024605041 hasConcept C17744445 @default.
- W2024605041 hasConcept C179518139 @default.
- W2024605041 hasConcept C188441871 @default.
- W2024605041 hasConcept C199539241 @default.
- W2024605041 hasConcept C201995342 @default.
- W2024605041 hasConcept C202444582 @default.
- W2024605041 hasConcept C2780451532 @default.
- W2024605041 hasConcept C33676613 @default.
- W2024605041 hasConcept C33923547 @default.
- W2024605041 hasConcept C41008148 @default.
- W2024605041 hasConcept C50644808 @default.
- W2024605041 hasConcept C66938386 @default.
- W2024605041 hasConcept C67203356 @default.
- W2024605041 hasConcept C97541855 @default.
- W2024605041 hasConceptScore W2024605041C105795698 @default.
- W2024605041 hasConceptScore W2024605041C110698143 @default.
- W2024605041 hasConceptScore W2024605041C127413603 @default.
- W2024605041 hasConceptScore W2024605041C154945302 @default.
- W2024605041 hasConceptScore W2024605041C17744445 @default.
- W2024605041 hasConceptScore W2024605041C179518139 @default.
- W2024605041 hasConceptScore W2024605041C188441871 @default.
- W2024605041 hasConceptScore W2024605041C199539241 @default.
- W2024605041 hasConceptScore W2024605041C201995342 @default.
- W2024605041 hasConceptScore W2024605041C202444582 @default.
- W2024605041 hasConceptScore W2024605041C2780451532 @default.
- W2024605041 hasConceptScore W2024605041C33676613 @default.
- W2024605041 hasConceptScore W2024605041C33923547 @default.
- W2024605041 hasConceptScore W2024605041C41008148 @default.
- W2024605041 hasConceptScore W2024605041C50644808 @default.
- W2024605041 hasConceptScore W2024605041C66938386 @default.
- W2024605041 hasConceptScore W2024605041C67203356 @default.
- W2024605041 hasConceptScore W2024605041C97541855 @default.
- W2024605041 hasLocation W20246050411 @default.
- W2024605041 hasOpenAccess W2024605041 @default.
- W2024605041 hasPrimaryLocation W20246050411 @default.
- W2024605041 hasRelatedWork W124072275 @default.
- W2024605041 hasRelatedWork W2024605041 @default.
- W2024605041 hasRelatedWork W2047937115 @default.
- W2024605041 hasRelatedWork W2107997647 @default.
- W2024605041 hasRelatedWork W2752108245 @default.
- W2024605041 hasRelatedWork W2888789309 @default.
- W2024605041 hasRelatedWork W2963673305 @default.
- W2024605041 hasRelatedWork W2969585312 @default.
- W2024605041 hasRelatedWork W3122963056 @default.
- W2024605041 hasRelatedWork W4281569697 @default.
- W2024605041 isParatext "false" @default.
- W2024605041 isRetracted "false" @default.
- W2024605041 magId "2024605041" @default.
- W2024605041 workType "article" @default.