Probabilistic programming for assessment of capability and capacity

Answering the questions "What can the adversary do?" and "What will the adversary do?" are critical functions of intelligence analysis. These questions require processing many sources of information, which is currently performed manually by analysts, leading to missed opportunities and potential mistakes. We have developed a system for Assessment of Capability and Capacity via Intelligence Analysis (ACACIA) to help analysts assess the capability, capacity, and intention of a nation state or non-state actor. ACACIA constructs a Bayesian network (BN) to model the objectives and means of an actor in a situation. However, a straightforward BN implementation is insufficient, since objectives and means are different in every situation. Additionally, we wish to apply knowledge about an element gained from one situation to another situation containing the same element. Furthermore, different elements of the same kind usually share the same model structure with different parameters. We use the probabilistic programming language Figaro, which allows models to be constructed using the power of programming languages, to address these issues, generating BNs for diverse situations while maximizing sharing. We learn the parameters of a program from training instances. Experiments show ACACIA is capable of making accurate inferences and that learning effectively improves ACACIA's performance.