We developed an agent-based model for deforestation to explore how agentsmake decisions associated with deforestation and how these decisions come toinfluence macro patterns of land-use over time. We assumed that a forest iscomposed of many land parcels arranged in a regular square lattice in aone-dimensional space. Each parcel is in either a forested or a deforestedstate. When utilities of forested and deforested states are given,landowners make decision to increase the net present value of their land.The net present value of the land is the weighting average of the currentutility and the utility to be received in a future. By analyzing equilibriumpatterns, we showed that when landowners largely discount the future, thedeforestation rate is very high and individual landowners tend to push theentire forest towards a deforested state. We gave the exact condition fordeforestation when landowners employed heuristic decision process. Based onthe result, we identify key factors that are important to facilitatesuccessful forest management.