We help plan a sustainable future for generations to come by designing, developing, and implementing policy-relevant computer simulation models that forecast social outcomes in contexts that include human interaction with nature. Our models apply SOSIEL (pronounced ˈsōSHəl and stands for Self-Organizing Social & Inductive Evolutionary Learning) theory, which describes the relationship among cognitive, behavioral, social, and demographic processes. Among the supporting resources is the open-source multi-agent SOSIEL Algorithm, which operationalizes SOSIEL theory and can be embedded within a spatiotemporal computer model to simulate cognitive agents that interact among themselves and with natural systems. Another resource is a work-in-progress textbook, titled Foundations of Modeling Coupled Human & Natural Systems: A Process- & Feedback-Oriented Approach. The textbook introduces the SOSIEL theory's and algorithm's foundations and applications, and is used as the main text in two undergraduate courses: Modeling Social-Ecological Systems and Introduction to Agent-Based Modeling. Please contact us with any questions, feedback, and/or suggestions.