  Learning and adaptation play great role in emergent socio-economic phenomena.
Complex dynamics has been previously found in the systems of multiple learning
agents interacting via a simple game. Meanwhile, the single agent adaptation is
considered trivially stable. We advocate the idea that adopting a more complex
model of the individual behavior may result in a more diverse spectrum of
macro-level behaviors. We develop an adaptation model based on the
reinforcement learning framework extended by an additional processing channel.
We scrutiny the dynamics of the single agent adapting to the unknown
environment; the agent is biased by novelty seeking, the intrinsic inclination
for exploration. We demonstrate that the behavior of the novelty-seeking agent
may be inherently unstable. One of the surprising results is that under certain
conditions the increase of the novelty-seeking level may cause the agent to
switch from the non-rational to the strictly rational behavior. Our results
give evidence to the hypothesis that the intrinsic motives of agents should be
paid no less attention than the extrinsic ones in the models of complex
socio-economic systems.

Physics and Society;Adaptation and Self-Organizing Systems