PAMELA is a probabilistic modeling language that extends the current state of the art process modeling languages, by adding first class probability variables. The language supports generative planning and temporal planning as well as supporting various learning algorithms for a more model-based approach than is possible with PDDL. Pamela is in use in numerous planning, learning, and social intelligence projects. Pamela can be compiled to produce HTN and TPN models and integrates with DOLL’s temporal and generative planners.