Transfer of knowledge across games is an aspect of learning which has been underresearched so far in Economics, but whose relevance and impact is growing exponentially for its connections with the design of artificial intelligence (AI). Despite the relevance of the topic, research within economics has been limited and focused on very specific frameworks, looking mostly at transfer across similar games, especially coordination games. Results have been contradictory. This research project contributes at expanding this limited literature in two ways: investigating how learned knowledge is transferred across different strategic situations and understanding to which extent learning is context dependent and manipulable. In particular, we aim at investigating the dynamics behind the process of transfer, unveiling the rules that drive the process of transfer of knowledge.