I have previously worked under the late Push Singh, who had developed the first working demonstration of Marvin Minsky's Emotion Machine cognitive architecture (the book, Introduction, Falling in Love [Ch. 1], Attachments and Goals [Ch. 2], From Pain to Suffering [Ch. 3], Consciousness [Ch. 4], Levels of Mental Activities [Ch. 5], Common Sense [Ch. 6], Thinking [Ch. 7], Resourcefulness [Ch. 8], The Self [Ch. 9], Bibliography). This implementation is interesting for many reasons. First, it was based on memories in the form of commonsense narratives, a humanly natural but complex form of memory. Also, the model is able to reflectively debug its own problem solving by using narratives of the mental processes themselves. Previous experiences are transfered from one mental problem solver to another through a structure mapping process called Parallel Analogy, or Panalogy. The process of panalogy is enabled by layers of reflective control structured in a critic-selector cognitive architecture. We design new programming languages that allow Causal Reflection over processes that exist in layers of control. Layers of reflective control allow near-miss one-shot learning algorithms to quickly adapt within very high-dimensional physical and social environments.

We are applying these powerful new forms for control systems to model how humans learn and adapt to their physical and social world in order to advance our cognitive science understanding of mental health. We strongly believe that a firm foundation in understanding mental health is an important prerequisite for understanding mental illness.