Spike-based Decision Learning of Nash Equilibria in Two-Player Games
Figure 1
Neuronal architecture implementing the two players.
Each player (
) is represented by a population of decision making neurons (shown
of each) which receive an input spike pattern
and generate an output spike pattern
. The population decision
is represented by a readout unit, with
being more likely when more decision making neurons fire at least one output spike. The synaptic weights
are adapted as a function of
,
,
and the reward signal
delivered by a critic.