Loading...
Please wait, while we are loading the content...
Similar Documents
Region-Based Incremental Pruning for POMDPs (2004)
| Content Provider | CiteSeerX |
|---|---|
| Author | Feng, Zhengzhu |
| Description | We present a major improvement to the incremental pruning algorithm for solving partially observable Markov decision processes. Our technique targets the cross-sum step of the dynamic programming (DP) update, a key source of complexity in POMDP algorithms. Instead of reasoning about the whole belief space when pruning the cross-sums, our algorithm divides the belief space into smaller regions and performs independent pruning in each region. We evaluate the benefits of the new technique both analytically and experimentally, and show that it produces very significant performance gains. The results contribute to the scalability of POMDP algorithms to domains that cannot be handled by the best existing techniques. |
| File Format | |
| Language | English |
| Publisher Date | 2004-01-01 |
| Publisher Institution | IN PROCEEDINGS OF THE 20TH CONFERENCE ON UNCERTAINTY IN ARTIFICIAL INTELLIGENCE (UAI2004 |
| Access Restriction | Open |
| Subject Keyword | Pomdp Algorithm Belief Space Significant Performance Gain Region-based Incremental Pruning Incremental Pruning Algorithm Key Source Dynamic Programming Observable Markov Decision Cross-sum Step New Technique Major Improvement Whole Belief Space |
| Content Type | Text |
| Resource Type | Article |
