  Interactions among individuals in natural populations often occur in a
dynamically changing environment. Understanding the role of environmental
variation in population dynamics has long been a central topic in theoretical
ecology and population biology. However, the key question of how individuals,
in the middle of challenging social dilemmas (e.g., the "tragedy of the
commons"), modulate their behaviors to adapt to the fluctuation of the
environment has not yet been addressed satisfactorily. Utilizing evolutionary
game theory and stochastic games, we develop a game-theoretical framework that
incorporates the adaptive mechanism of reinforcement learning to investigate
whether cooperative behaviors can evolve in the ever-changing group interaction
environment. When the action choices of players are just slightly influenced by
past reinforcements, we construct an analytical condition to determine whether
cooperation can be favored over defection. Intuitively, this condition reveals
why and how the environment can mediate cooperative dilemmas. Under our model
architecture, we also compare this learning mechanism with two non-learning
decision rules, and we find that learning significantly improves the propensity
for cooperation in weak social dilemmas, and, in sharp contrast, hinders
cooperation in strong social dilemmas. Our results suggest that in complex
social-ecological dilemmas, learning enables the adaptation of individuals to
varying environments.
