  In this paper we show that behavioral cloning can be used to learn effective
sketches of programmatic strategies. We show that even the sketches learned by
cloning the behavior of weak players can help the synthesis of programmatic
strategies. This is because even weak players can provide helpful information,
e.g., that a player must choose an action in their turn of the game. If
behavioral cloning is not employed, the synthesizer needs to learn even the
most basic information by playing the game, which can be computationally
expensive. We demonstrate empirically the advantages of our sketch-learning
approach with simulated annealing and UCT synthesizers. We evaluate our
synthesizers in the games of Can't Stop and MicroRTS. The sketch-based
synthesizers are able to learn stronger programmatic strategies than their
original counterparts. Our synthesizers generate strategies of Can't Stop that
defeat a traditional programmatic strategy for the game. They also synthesize
strategies that defeat the best performing method from the latest MicroRTS
competition.
