Dynamic Treatment Regimes (DTRs) are of growing interest across the clinical sciences as they provide sequential, personalized decision making. Traditional DTRs recommend only one treatment at each decision point. This might not always be a good choice since there is often insufficient evidence to differentiate between several ``best'' treatments. Instead, we would like to offer patients a set of treatments if we have no evidence to distinguish among them. Then the patients can choose among the treatments in the set according to their own preference. Our method is based on the Multiple Comparisons with the Best technique. First we define the ``effect'' of a treatment. A treatment is included in the recommended set if we cannot reject the null hypothesis that this treatment's effect is no worse than each of the other available treatments' effect. We will also discuss how to utilize the Adaptive Confidence Interval technique across sequential decision points.