One of the advantages of the remote sensing method is that it minimizes surface surveys, especially in inaccessible areas based on spectral information obtained from satellite images. The presence of minerals can be explored by their spectral signatures recorded in satellite images. The main hypothesis of this research is that the combination of such processes with agent-based modeling (ABM) can lead to better planning of the mining exploration and reduce cost and time. In this study, ASTER and OLI sensors were used to identify areas containing minerals in the Yanesar section of Behshahr city. Due to the combination of mineralogy and lithology, the study area is mainly made of lime, shale, clay, and marl. The result of the processing is the exposure of lime units. After pre-processing on the information and satellite images, band ratio methods have been used to identify areas with lime mineral potential. Then, Spectral Angle Mapper (SAM) method was used to more accurately separate these areas using the USGS laboratory spectral library. In order to optimize time and cost in order to identify areas containing lime minerals, agent-based modeling has been used as a new approach. By considering several strategies based on random movement and movement in mineral potential areas, time tables and cost were obtained and compared with each other, and finally, the best results in terms of time, cost, and a number of explorer agents were obtained.