  We investigate adaptive single-trial error/erasure decoding of binary codes
whose decoder is able to correct e errors and t erasures if le+t<=d-1. Thereby,
d is the minimum Hamming distance of the code and 1<l<=2 is the tradeoff
parameter between errors and erasures. The error/erasure decoder allows to
exploit soft information by treating a set of most unreliable received symbols
as erasures. The obvious question here is, how this erasing should be
performed, i.e. how the unreliable symbols which must be erased to obtain the
smallest possible residual codeword error probability are determined. In a
previous paper, we answer this question for the case of fixed erasing, where
only the channel state and not the individual symbol reliabilities are taken
into consideration. In this paper, we address the adaptive case, where the
optimal erasing strategy is determined for every given received vector.
