Maximizing a reward can be formulated as minimizing its negative. This transformation allows the problem to fit into standard optimization frameworks that typically focus on minimization, while still requiring the specification of feasible choices via constraints.
Conditions: The goal is to maximize a reward function.; The optimization framework is set up for minimization.; Feasible choices are still constrained by equalities or inequalities.
Maximizing a reward can be formulated as minimizing its negative. This transformation allows the problem to fit into standard optimization frameworks that typically focus on minimization, while still requiring the specification of feasible choices via constraints.
Conditions: The goal is to maximize a reward function.; The optimization framework is set up for minimization.; Feasible choices are still constrained by equalities or inequalities.