Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs
This article presents the state-of-the-art in optimal solution methods for decentralized partially observable Markov decision processes (Dec-POMDPs), which are general models for collaborative multiagent planning under uncertainty. Building off the generalized multiagent A* (GMAA*) algorithm, which...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Association for the Advancement of Artificial Intelligence,
2013-09-16T16:38:43Z.
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| Subjects: | |
| Online Access: | Get fulltext |