Pareto Monte Carlo Tree Search for Multi-Objective Informative Planning Article Swipe
Weizhe Chen
,
Lantao Liu
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2111.01825
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2111.01825
In many environmental monitoring scenarios, the sampling robot needs to simultaneously explore the environment and exploit features of interest with limited time. We present an anytime multi-objective informative planning method called Pareto Monte Carlo tree search which allows the robot to handle potentially competing objectives such as exploration versus exploitation. The method produces optimized decision solutions for the robot based on its knowledge (estimation) of the environment state, leading to better adaptation to environmental dynamics. We provide algorithmic analysis on the critical tree node selection step and show that the number of times choosing sub-optimal nodes is logarithmically bounded and the search result converges to the optimal choices at a polynomial rate.
Related Topics
Concepts
Monte Carlo tree search
Computer science
Monte Carlo method
Pareto principle
Exploit
Mathematical optimization
Tree (set theory)
Sampling (signal processing)
Node (physics)
Robot
Pareto optimal
Multi-objective optimization
Machine learning
Artificial intelligence
Mathematics
Engineering
Statistics
Computer vision
Structural engineering
Filter (signal processing)
Mathematical analysis
Computer security
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/pdf/2111.01825.pdf
- OA Status
- green
- Cited By
- 2
- References
- 28
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3210014884
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3210014884Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2111.01825Digital Object Identifier
- Title
-
Pareto Monte Carlo Tree Search for Multi-Objective Informative PlanningWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-11-02Full publication date if available
- Authors
-
Weizhe Chen, Lantao LiuList of authors in order
- Landing page
-
https://arxiv.org/pdf/2111.01825.pdfPublisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2111.01825.pdfDirect OA link when available
- Concepts
-
Monte Carlo tree search, Computer science, Monte Carlo method, Pareto principle, Exploit, Mathematical optimization, Tree (set theory), Sampling (signal processing), Node (physics), Robot, Pareto optimal, Multi-objective optimization, Machine learning, Artificial intelligence, Mathematics, Engineering, Statistics, Computer vision, Structural engineering, Filter (signal processing), Mathematical analysis, Computer securityTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 2Per-year citation counts (last 5 years)
- References (count)
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28Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
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| cited_by_percentile_year.min | 94 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.7300000190734863 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.64234063 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |