Techniques described herein relate to applying reinforcement learning to improve engagement with counseling chatbots. In various embodiments, based on a first state of a subject and a decision model (109), a given natural language response may be selected (404) from a plurality of candidate natural language responses and provided to the user by the counseling chatbot. A free-form natural language input may be received (408) from the subject at one or more input components of one or more computing devices. A second state of the subject may be determined (410) based on speech recognition output generated from the free-from natural language input. The second state may be a positive, negative, or neutral valance towards a target behavior change. Based on the second state, and instant reward may be calculated (412) and used to train (414) the decision model.
Techniques for improving turn-based automated counseling to alter behavior