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This book introduces a general framework for sensitivity analysis in multi-objective decision making. It deals with decision making under partial information. The proper axiomatic foundations are developed, a convenient paramentric model is introduced and the adequate solution concepts are analysed, together with algorithms to compute them. In summary, a robust coherent theory of decision making, new sensitivity tools based on gauge functions and Bayesian hypothesis testing, and a description of its implementation are included. The implementation of this framework is described, proving its feasibility, power and success.