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A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments
The aim of this work is to produce and test a robust, distributed, mul-ti-agent task allocation algorithm, as these are scarce and not well-documented in the literature. The vehicle used to create the robust system is the Performance Impact algorithm (PI), as it has previously shown good performance...
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| Main Authors: | , , |
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| Format: | Default Conference proceeding |
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2017
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| Subjects: | |
| Online Access: | https://hdl.handle.net/2134/24597 |
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| _version_ | 1818171294733041664 |
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| author | Amanda Whitbrook Qinggang Meng Paul Chung |
| author_facet | Amanda Whitbrook Qinggang Meng Paul Chung |
| author_sort | Amanda Whitbrook (711308) |
| collection | Figshare |
| description | The aim of this work is to produce and test a robust, distributed, mul-ti-agent task allocation algorithm, as these are scarce and not well-documented in the literature. The vehicle used to create the robust system is the Performance Impact algorithm (PI), as it has previously shown good performance. Three dif-ferent variants of PI are designed to improve its robustness, each using Monte Carlo sampling to approximate Gaussian distributions. Variant A uses the ex-pected value of the task completion times, variant B uses the worst-case scenar-io metric and variant C is a hybrid that implements a combination of these. The paper shows that, in simulated trials, baseline PI does not handle uncertainty well; the task-allocation success rate tends to decrease linearly as degree of un-certainty increases. Variant B demonstrates a worse performance and variant A improves the failure rate only slightly. However, in comparison, the hybrid var-iant C exhibits a very low failure rate, even under high uncertainty. Further-more, it demonstrates a significantly better mean objective function value than the baseline. |
| format | Default Conference proceeding |
| id | rr-article-9405512 |
| institution | Loughborough University |
| publishDate | 2017 |
| record_format | Figshare |
| spelling | rr-article-94055122017-01-01T00:00:00Z A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments Amanda Whitbrook (711308) Qinggang Meng (1257072) Paul Chung (1250973) Other information and computing sciences not elsewhere classified untagged Information and Computing Sciences not elsewhere classified The aim of this work is to produce and test a robust, distributed, mul-ti-agent task allocation algorithm, as these are scarce and not well-documented in the literature. The vehicle used to create the robust system is the Performance Impact algorithm (PI), as it has previously shown good performance. Three dif-ferent variants of PI are designed to improve its robustness, each using Monte Carlo sampling to approximate Gaussian distributions. Variant A uses the ex-pected value of the task completion times, variant B uses the worst-case scenar-io metric and variant C is a hybrid that implements a combination of these. The paper shows that, in simulated trials, baseline PI does not handle uncertainty well; the task-allocation success rate tends to decrease linearly as degree of un-certainty increases. Variant B demonstrates a worse performance and variant A improves the failure rate only slightly. However, in comparison, the hybrid var-iant C exhibits a very low failure rate, even under high uncertainty. Further-more, it demonstrates a significantly better mean objective function value than the baseline. 2017-01-01T00:00:00Z Text Conference contribution 2134/24597 https://figshare.com/articles/conference_contribution/A_robust_distributed_task_allocation_algorithm_for_time-critical_multi_agent_systems_operating_in_uncertain_environments/9405512 CC BY-NC-ND 4.0 |
| spellingShingle | Other information and computing sciences not elsewhere classified untagged Information and Computing Sciences not elsewhere classified Amanda Whitbrook Qinggang Meng Paul Chung A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments |
| title | A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments |
| title_full | A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments |
| title_fullStr | A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments |
| title_full_unstemmed | A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments |
| title_short | A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments |
| title_sort | robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments |
| topic | Other information and computing sciences not elsewhere classified untagged Information and Computing Sciences not elsewhere classified |
| url | https://hdl.handle.net/2134/24597 |