  In this paper, we introduce a novel MCTS based approach that is derived from
the laws of the thermodynamics. The algorithm coined Fractal Monte Carlo (FMC),
allows us to create an agent that takes intelligent actions in both continuous
and discrete environments while providing control over every aspect of the
agent behavior. Results show that FMC is several orders of magnitude more
efficient than similar techniques, such as MCTS, in the Atari games tested.
