Steering Evolution Strategically: Computational Game Theory and Opponent Exploitation for Treatment Planning, Drug Design, and Synthetic Biology

Living organisms adapt to challenges through evo-lution and adaptation. This has proven to be a key difficulty in developing therapies, since the organ-isms develop resistance. I propose the wild idea of steering evolution/adaptation strategically—using computational game theory for (typically incomplete-information) multistage games and opponent exploita-tion techniques. A sequential contingency plan for steer-ing is constructed computationally for the setting at hand. In the biological context, the opponent (e.g., a disease) has a systematic handicap because it evolves myopically. This can be exploited by computing trap-ping strategies that cause the opponent to evolve into states where it can be handled effectively. Potential ap