*Use of the Greedy Algorithm and Reinforcement Learning to Devise Optimum Plant Conservation Plan (2020)

Biodiversity and conservation of different organisms is crucial to preserve the elaborate balance of the ecosystem. However, the current conservation endowments are not being distributed in the most efficient way due to the constraints imposed on the amount of funds. A new scheme is imperative for a more efficient conservation for the biodiversity of plants.

 

In this paper we aim to construct a model which takes into account all the factors the board may consider when selecting the plants to subsidize. To achieve this objective, we implemented the use of two different models. We inferred from the level of availability of funds that the current method was unsuccessful in conserving the most number of species while utilizing the minimum cost. Having a multi model approach was used to our benefit as we could compare the results from both approaches and calculate a value that was closest to the true optimal combination.