Indian Institute of Technology (IIT) Madras and Harvard University researchers have developed a novel Machine Learning algorithm named ‘CombSGPO’ (Combined Security Game Policy Optimization) to save wildlife from poaching.
This new algorithm provides highly efficient strategies that are more scalable than the earlier ones created for the same purpose, IIT Madras said.
“The algorithm works by handling resource allocation and strategizing patrolling after the extent of resources available had been identified. For this task, it utilizes data on the animal population in the conserved area and assumes that poachers are aware about the patrolling being done at various sites,” IIT Madras said in a press release.
The institute further said the work has been peer reviewed and was well received at the 20th International Conference on Autonomous Agents and Multi-Agent Systems.
Prof. Balaraman Ravindran of Department of Computer Science and Engineering, IIT Madras collaborated with Prof. Milind Tambe’s Research Group Teamcore at Harvard University to carry out this study.
Highlighting the need for such Research, Prof. Ravindran, said, “The work was motivated by the need to perform strategic resource allocation and patrolling in green security domains to prevent illegal activities such as wildlife poaching, illegal logging and illegal fishing.
“The resources we consider are human patrollers (forest rangers) and surveillance drones, which have object detectors mounted on them for animals and poachers and can perform strategic signalling and communicate with each other as well as the human patrollers,” he added.