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Standard models in bio-evolutionary game theory involve repetitions of a single stage game (e.g., the Prisoner's Dilemma or the Stag Hunt); but it is clear that repeatedly playing the same stage game is not an accurate model of most individuals' lives. Rather, individuals' interactions with others correspond to many different kinds of stage games. In this work, we concentrate on discovering behavioral strategies that are successful for the life game, in which the stage game is chosen stochastically at each iteration. We present a cognitive agent model based on Social Value Orientation (SVO) theory. We provide extensive evaluations of our model's performance, both against standard agents from the game theory literature and against a large set of life-game agents written by students in two different countries. Our empirical results suggest that for life-game strategies to be successful in environments with such agents, it is important (i) to be unforgiving with respect to trust behavior and (ii) to use adaptive, fine-grained opponent models of the other agents.