  Understanding how knowledge is created and propagates within groups is
crucial to explain how human populations have evolved through time.
Anthropologists have relied on different theoretical models to address this
question. In this work, we introduce a mathematically oriented model that
shares properties with individual based approaches, inhomogeneous Markov chains
and learning algorithms, such as those introduced in [F. Cucker, S. Smale,
Bull. Amer. Math. Soc., 39 (1), 2002] and [F. Cucker, S. Smale and D.~X Zhou,
Found. Comput. Math., 2004]. After deriving the model, we study some of its
mathematical properties, and establish theoretical and quantitative results in
a simplified case. Finally, we run numerical simulations to illustrate some
properties of the model.
