Richard Sutton presents 49th Prague Computer Science Seminar: The Alberta Plan for AI Research

The speaker will present a strategic research plan based on the premise that a
genuine understanding of intelligence is imminent and—when it is
achieved—will be the greatest scientific prize in human history. To
contribute
to this achievement and share in its glory will require laser-like focus on its
essential challenges; identifying those, however provisionally, is the
objective
of the Alberta Plan for AI research. The overall setting is the familiar one
common to many fields (reinforcement learning, psychology, control theory,
economics, neuroscience, and operations research): a computationally-limited
agent interacts with a vastly more complex environment to maximize reward. The
agent’s machinery is divided into four parts: 1) that which maintains the
agent’s situational state (perception), 2) that which maps state to action
(policy), 3) that which maps state to expected future reward (value function),
and 4) that which maps imagined states and actions to next states (transition
model) and enables planning. The Alberta Plan extends this common view to
include feature-based subtasks and temporally extended options to solve them;
the policy and the value function each become multiple, one each for each of
the
subtasks and the main task. The setting is then potentially complete and the
focus shifts to finding the right abstractions, in state (features) and time
(options), and to planning efficiency. The Alberta Plan incorporates continual
learning and meta-learning into all of its 12 steps, and expends no effort
trying to capture domain knowledge.
https://www.praguecomputerscience.cz/?l=en&p=49