Some mental states have valence—they are pleasant or unpleasant. According to imperativism, valence depends on imperative content, while evaluativism tells us that it depends on evaluative content. We argue that if one considers valence’s informational profile, it becomes evident that imperativism is superior to evaluativism. More precisely, we show that if one applies the best available metasemantics to the role played by (un)pleasant mental states in our cognitive economy, then these states turn out to have imperative rather than evaluative content, (...) since: (i) they are much more informative about behaviour than they are about the world; and (ii) they occupy a stage in the information-processing chain that is closer to behaviour production than it is to the uptake of sensory information. This is our metasemantic argument for imperativism. (shrink)

I argue for the role of reinforcement learning in the philosophy of mind. To start, I make several assumptions about the nature of reinforcement learning and its instantiation in minds like ours. I then review some of the contributions of reinforcement learning methods have made across the so-called 'decision sciences.' Finally, I show how principles from reinforcement learning can shape philosophical debates regarding the nature of perception and characterisations of desire.

In this opinionated review, I draw attention to some of the contributions reinforcement learning can make to questions in the philosophy of mind. In particular, I highlight reinforcement learning's foundational emphasis on the role of reward in agent learning, and canvass two ways in which the framework may advance our understanding of perception and motivation.

Affective valence is increasingly thought to be the common currency underlying all forms of intuitive, non-discursive decision making, in both humans and other animals. And it is thought to constitute the good or bad (pleasant or unpleasant) aspects of all desires, emotions, and moods. This article contrasts two theories of valence. According to one, valence is an experience-directed imperative (‘more of this!’ or ‘less of this!’); according to the other, valence is a representation of adaptive value or disvalue. The latter (...) is shown to provide the better account. (shrink)

I propose that the successes and contributions of reinforcement learning urge us to see the mind in a new light, namely, to recognise that the mind is fundamentally evaluative in nature.