  The premise of the Multi-disciplinary Conference on Reinforcement Learning
and Decision Making is that multiple disciplines share an interest in
goal-directed decision making over time. The idea of this paper is to sharpen
and deepen this premise by proposing a perspective on the decision maker that
is substantive and widely held across psychology, artificial intelligence,
economics, control theory, and neuroscience, which I call the "common model of
the intelligent agent". The common model does not include anything specific to
any organism, world, or application domain. The common model does include
aspects of the decision maker's interaction with its world (there must be input
and output, and a goal) and internal components of the decision maker (for
perception, decision-making, internal evaluation, and a world model). I
identify these aspects and components, note that they are given different names
in different disciplines but refer essentially to the same ideas, and discuss
the challenges and benefits of devising a neutral terminology that can be used
across disciplines. It is time to recognize and build on the convergence of
multiple diverse disciplines on a substantive common model of the intelligent
agent.
