Integrating Planning, Execution and Monitoring in the presence of Open
  World Novelties: Case Study of an Open World Monopoly Solver
  The game of monopoly is an adversarial multi-agent domain where there is no
fixed goal other than to be the last player solvent, There are useful subgoals
like monopolizing sets of properties, and developing them. There is also a lot
of randomness from dice rolls, card-draws, and adversaries' strategies. This
unpredictability is made worse when unknown novelties are added during
gameplay. Given these challenges, Monopoly was one of the test beds chosen for
the DARPA-SAILON program which aims to create agents that can detect and
accommodate novelties. To handle the game complexities, we developed an agent
that eschews complete plans, and adapts it's policy online as the game evolves.
In the most recent independent evaluation in the SAILON program, our agent was
the best performing agent on most measures. We herein present our approach and
results.
