This chapter defends a cognitive-efficiency-based account of the evolution of conative representational decision making. The core idea behind this account is that, similarly to cognitive representational decision makers, conative representational decision makers can, in some circumstances, adjust more easily to a changed environment and streamline their neural decision making machinery. However, as I also make clearer, the origins of these benefits are different here than in the case of cognitive representational decision making: they center on patterns in the way the organism reacts to the world, and not on patterns in the states of the world that the organism can react to. This has some important implications for the situations in which conative representational decision making is adaptive relative to when cognitive representational decision making is adaptive. The chapter ends by combining the picture laid out here with that laid out in the previous chapter to develop a clearer account of the relationship between the evolution of conative and the evolution of cognitive representational decision making.

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Three facts are widely thought to be key to the characterization of human cognitive uniqueness (though a number of other factors are often cited as well): (a) humans are sophisticated cultural learners; (b) humans often rely on mental states with rich representational contents; and (c) humans have the ability and disposition to make and use tools. This article argues that (a)-(c) create a positive feedback loop: Sophisticated cultural learning makes possible the manufacture of tools that increase the sophistication of representational decision-making, which in turn allows for yet further increases in the sophistication of cultural learning and tool manufacture.