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| Content Provider | ACM Digital Library |
|---|---|
| Author | Oral, Tugcem Polat, Faruk |
| Abstract | Path planning is a crucial issue in unknown environments where an autonomous mobile agent has to reach a particular destination from some initial location. There are several incremental algorithms such as D* [1], D* Lite [2] that are able to ensure reasonable paths in terms of path length in unknown environments. However, in many real-world problems we realize that path length is not only the sole objective. For example in computer games, a non-player character needs to not only find a minimum cost path to some target location but also minimize threat exposure. This means that path planning/finding activity of an agent in a multi-agent environment has to consider more than one objective to be achieved. In this paper, we propose a new incremental search algorithm called MOD* Lite extending Koenig's D* Lite algorithm and show that MOD* Lite is able to optimize path quality in more than one criteria that cannot be transformed to each other. Experimental results show that MOD* Lite is able to find optimal solutions and is fast enough to be used in real-world multi-agent applications such as robotics, computer games, or virtual simulations. |
| Starting Page | 401 |
| Ending Page | 408 |
| Page Count | 8 |
| File Format | |
| ISBN | 9780769548807 |
| DOI | 10.1109/WI-IAT.2012.143 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-12-04 |
| Access Restriction | Subscribed |
| Subject Keyword | Path planning multi-objectivity incremental search algorithm |
| Content Type | Text |
| Resource Type | Article |
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