Training Data Set Assessment for Decision-Making in a Multiagent Landmine Detection Platform
| dc.cclicence | CC-BY-NC | en |
| dc.contributor.author | Florez-Lozano, Johana | |
| dc.contributor.author | Caraffini, Fabio | |
| dc.contributor.author | Parra, Carlos | |
| dc.contributor.author | Gongora, Mario Augusto | |
| dc.date.acceptance | 2020-03-20 | |
| dc.date.accessioned | 2020-06-02T09:00:36Z | |
| dc.date.available | 2020-06-02T09:00:36Z | |
| dc.date.issued | 2020-07-19 | |
| dc.description.abstract | Real-world problems such as landmine detection require multiple sources of information to reduce the uncertainty of decision-making. A novel approach to solve these problems includes distributed systems, as presented in this work based on hardware and software multi-agent systems. To achieve a high rate of landmine detection, we evaluate the performance of a trained system over the distribution of samples between training and validation sets. Additionally, a general explanation of the data set is provided, presenting the samples gathered by a cooperative multi-agent system developed for detecting improvised explosive devices. The results show that input samples affect the performance of the output decisions, and a decision-making system can be less sensitive to sensor noise with intelligent systems obtained from a diverse and suitably organised training set. | en |
| dc.funder | No external funder | en |
| dc.identifier.citation | Florez-Lozano, J., Cariffini, F., Parra, C., Gongora, M.A. (2020) Training Data Set Assessment for Decision-Making in a Multiagent Landmine Detection Platform. IEEE World Congress on Computational Intelligence (WCCI), Glasgow, UK., July 2020. | en |
| dc.identifier.uri | https://sites.google.com/site/facaraff/research/gcrf18 | |
| dc.identifier.uri | https://dora.dmu.ac.uk/handle/2086/19683 | |
| dc.language.iso | en | en |
| dc.peerreviewed | Yes | en |
| dc.projectid | Colciencias, Colombia, grant number 647, 2014 | en |
| dc.projectid | Pontificia Universidad Javeriana, Bogota, Colombia, grant number VRI-05, 2017 | en |
| dc.projectid | DMU Global Challenges Research Funds 2019/2020 | en |
| dc.publisher | IEEE | en |
| dc.researchinstitute | Institute of Artificial Intelligence (IAI) | en |
| dc.subject | Land mine detection | en |
| dc.subject | improvised explosive device | en |
| dc.subject | neuroevolution | en |
| dc.subject | genetic fuzzy systems | en |
| dc.subject | decision making | en |
| dc.title | Training Data Set Assessment for Decision-Making in a Multiagent Landmine Detection Platform | en |
| dc.type | Conference | en |