NTT Research Scientist Creates Model for Discontinuous Learning
Dr. Reddy shows that the outcome of reinforcement learning (RL) algorithms, which operate gradually, can appear discontinuous for certain kinds of tasks.
- Dr. Reddy shows that the outcome of reinforcement learning (RL) algorithms, which operate gradually, can appear discontinuous for certain kinds of tasks.
- “We show that the nonlinear dynamics of RL-based learning, together with continuous exploration, lead to discontinuous learning curves in tree-like structured environments,” Dr. Reddy said.
- Along with these research initiatives, Dr. Reddy also serves as the NTT Research PHI Lab lead on a five-year joint research project with scientists at Harvard University to study animal neuro-responses, in the hope of informing future artificial intelligence (AI) systems.
- The NASA Ames Research Center in Silicon Valley has also entered into a joint research agreement with the PHI Lab.