# General-Sum Games

Methods that shape how an opponent learns in general-sum games have needed access to that opponent's policy, parameters or learning rule. A study carries the single-agent practice of meta-learning an update rule into multi-agent play, meta-training a rule that reads only the agent's own experience and payoff matrix, so deployment needs no privileged opponent information. Across round-robin tournaments in Prisoner's Dilemma, Matching Pennies, Chicken, Stag Hunt and Coin Game, the rule ranks first in normalised mean score over all five games and first in self-play.

Methods that shape how an opponent learns in general-sum games have needed access to that opponent's policy, parameters or learning rule. A study carries the single-agent practice of meta-learning an update rule into multi-agent play, meta-training a rule that reads only the agent's own experience and payoff matrix, so deployment needs no privileged opponent information. Across round-robin tournaments in Prisoner's Dilemma, Matching Pennies, Chicken, Stag Hunt and Coin Game, the rule ranks first in normalised mean score over all five games and first in self-play.