https://www.researchgate.net/publication/331159396_INVERSE_REINFORCEMENT_LEARNING_CONDITIONED_ON_BRAIN_SCAN
I outline a way for an agent to learn the dispositions of a particular individual through inverse reinforcement learning where the state space at time t includes an fMRI scan of the individual, to represent his brain state at that time. The fundamental assumption being that the information shown on an fMRI scan of an individual is conditioned on his thoughts and thought processes. The system models both long and short term memory as well any internal dynamics we may not be aware of that are in the human brain. The human expert will put on a suit for a set duration with sensors whose information will be used to train a policy network, while a generative model will be trained to produce the next fMRI scan image conditioned on the present one and the state of the environment. During operation the humanoid robots actions will be conditioned on this evolving fMRI and the environment it is in. -- You received this message because you are subscribed to the Google Groups "opencog" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/opencog. To view this discussion on the web visit https://groups.google.com/d/msgid/opencog/ce6e2ae6-9ff4-4b29-8f60-0af995582bce%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
