For agents like us, the feeling of effort is a very useful thing. It helps us sense how hard an action is, control its level of intensity, and decide whether to continue or stop performing it. While there has been progress in understanding the feeling of mental effort and the feeling of bodily effort, this has not translated into a unified account of the general feeling of effort. To advance in this direction, I defend the single-feeling view, which states that (...) the feeling of effort is one and the same for both mental and bodily actions. This feeling represents the subjective costs, both mental and physical, of performing a given action. Cost-based approaches have recently become influential for the feeling of mental effort. Here I focus on arguing that our sense of bodily effort does not simply represent physiological processes, but rather represents the subjective costs of a bodily action. Through this paper I discuss the role of the feeling of effort (and affective states more broadly) in action guidance and the sense of agency. I also define efforts themselves in terms of the feeling of effort. (shrink)

Multiple Authors - please see paper attached. -/- AI systems have seen dramatic advancement in recent years, bringing many applications that pervade our everyday life. However, we are still mostly seeing instances of narrow AI: many of these recent developments are typically focused on a very limited set of competencies and goals, e.g., image interpretation, natural language processing, classification, prediction, and many others. We argue that a better study of the mechanisms that allow humans to have these capabilities can help (...) us understand how to imbue AI systems with these competencies. We focus especially on D. Kahneman’s theory of thinking fast and slow , and we propose a multi-agent AI architecture (called SOFAI, for SlOw and Fast AI) where incoming problems are solved by either system 1 (or "fast") agents (also called "solvers"), that react by exploiting only past experience, or by system 2 (or "slow") agents, that are deliberately activated when there is the need to reason and search for optimal solutions beyond what is expected from the system 1 agent. (shrink)

The broad spectrum revolution brought greater dependence on skill and knowledge, and more demanding, often social, choices. We adopt Sterelny's account of how cooperative foraging paid the costs associated with longer dependency, and transformed the problem of skill learning. Scaffolded learning can facilitate cognitive control including suppression, whereas scaffolded exchange and trade, including inter-temporal exchange, can help develop resolve.

In “Willpower with and without effort”, G. Ainslie advances our understanding of selfcontrol by theoretically unifying multiple forms of willpower. But one crucial question remains unanswered: How do agents pick the right forms of willpower in each situation? I argue that willpower requires tactical skill, which detects willpower-demanding contexts, selects context-appropriate tactics, and monitors their implementation. Research on tactical skill will significantly advance our understanding of willpower.

While the term “metacognition” is sometimes used to refer to any form of thinking about thinking, in cognitive psychology, it is typically reserved for thinking about one’s own thinking, as opposed to thinking about others’ thinking. How metacognition in this more specific sense relates to other-directed mindreading is one of the main theoretical issues debated in the literature. This article considers the idea that we make use of the same or a largely similar package of resources in conceptually interpreting our (...) own mind as we do in interpreting others’. I assume that a capacity for other-directed mindreading is minimally shared with our great-ape relatives, but I argue that the architecture of this system had to be substantially modified before it could efficiently and adaptively be turned inwards on one’s own mind. I contend that an important piece of the overall evolutionary explanation here likely concerns selection pressures arising from the domain of conversational interaction. Specifically, drawing on work carried out in the human interaction studies tradition (e.g., conversation analysis), I argue that the smooth to-and-fro of conversational interaction can be seen to heavily depend on metacommunicative capacities, which, in turn, are underpinned by metacognitive capacities. I conclude with a thumbnail sketch of an evolutionary account of the emergence of these metacognitive capacities in the human line. Their appearance and spread – whether via genes, cultural learning, or more likely, some combination of the two – helps to explain the transition from great-ape communication to human conversation. (shrink)