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Automated bilateral agent negotiation under uncertainty, that is with imprecise or uncertain information about preferences, utilities and strategies of the opponent is known to be hard. In this paper, we present the first adaptive solution that bases on multistage fuzzy decision making. The modelling of individual preferences as fuzzy goal and fuzzy constraints, and observed strategic concession behaviour of opponents during negotiation as a fuzzy Markov decision process allows the agent to adapt its negotiation strategies and implied behaviour to improve its individual payoffs. In particular, we show that such adaptive bilateral negotiation strategies can be efficiently derived by an agent from negotiation threads of only two reference cases in its respectively maintained fuzzy transition matrix. Finally, we demonstrate the benefit of applying this solution to different soft-constrained negotiation settings by an initial comparative experimental evaluation.