  In Evolutionary Game Theory (EGT), a population reaches a Nash equilibrium
when none of the agents can improve its objective by solely changing its
strategy on its own. Roughly speaking, this equilibrium is a protection against
betrayal. Generalized Nash Equilibrium (GNE) is a more complex version of this
idea with important implications in real-life problems in economics, wireless
communication, the electricity market, or engineering among other areas. In
this paper, we propose a first approach to GNE with Membrane Computing
techniques and show how GNE problems can be modeled with P systems, bridging
both areas and opening a door for a flow of problems and solutions in both
directions.
