  Learning models do not in general imply that weakly dominated strategies are
irrelevant or justify the related concept of "forward induction," because
rational agents may use dominated strategies as experiments to learn how
opponents play, and may not have enough data to rule out a strategy that
opponents never use. Learning models also do not support the idea that the
selected equilibria should only depend on a game's normal form, even though two
games with the same normal form present players with the same decision problems
given fixed beliefs about how others play. However, playing the extensive form
of a game is equivalent to playing the normal form augmented with the
appropriate terminal node partitions so that two games are information
equivalent, i.e., the players receive the same feedback about others'
strategies.
