  We consider an adaptive finite element method with arbitrary but fixed
polynomial degree $p \ge 1$, where adaptivity is driven by an edge-based
residual error estimator. Based on the modified maximum criterion from [Diening
et al, Found. Comput. Math. 16, 2016], we propose a goal-oriented adaptive
algorithm and prove that it is instance optimal. More precisely, the goal-error
is bounded by the product of the total errors (being the sum of energy error
plus data oscillations) of the primal and the dual problem, and the proposed
algorithm is instance optimal with respect to this upper bound. Numerical
experiments underline our theoretical findings.
