My fundamental objective is to maximize the wellbeing of intelligences that experience subjectively positive and negative states of consciousness. To realize this goal, I simulate and analyze artificial societies populated with cognitively, emotionally, and socially plausible agents. To develop these agents, I plan to (a) utilize the Neural Engineering Framework to specify how biological brains represent and process information, (b) construct human-like agents by incorporating emotional and social modules into SPAUN, and (c) generate unique personalities for these agents by exposing them to unique developmental regimes. With unlimited access to information in the simulation, I can (d) define quantitative measures of an agent's wellbeing based on its observed brain state. To maximize this quantity across an (e) artificial society composed of agents situated in a virtual environment, I will (f) design controlled experiments that investigate the personal and societal conditions which promote the greatest wellbeing, and finally (g) apply these results back to our reality for the same purpose.
In my masters work at the University of Waterloo, I plan to model the effects of drugs on emotional systems, specifically the amygdala, using biologically-detailed neuron models; this is the first step towards understanding the neuromodulatory control these systems exert over other cognitive processes, including those governing social interaction. In my doctoral work, I hope to engineer agents capable of emotionally-biased cognition and communication through a combination of neural engineering and reinforcement learning, with the goal of reproducing small-N experiments in social psychology.