According to the Causal Theory of Action (CTA), genuine actions are individuated by their causal history. Actions are bodily movements that are causally explained by citing the agent’s reasons. Reasons are then explained as some combination of propositional attitudes – beliefs, desires, and/or intentions. The CTA is thus committed to realism about the attitudes. This paper explores current models of decision-making from the mind sciences, and argues that it is far from obvious how to locate the propositional attitudes in the (...) causal processes they describe. The outcome of the analysis is a proposal for pluralism: there are several ways one could attempt to map states like “intention” onto decision-making processes, but none will fulfill all of the roles attributed to the attitudes by the CTA. (shrink)

Neuroscientists have located brain activity that prepares or encodes action plans before agents are aware of intending to act. On the basis of these findings and broader agency research, activity in these regions has been proposed as the neural realizers of practical intention. My aim in this paper is to evaluate the case for taking these neural states to be neural representations of intention. I draw on work in philosophy of action on the role and nature of practical intentions to (...) construct a framework of the functional profile of intentions fit for empirical investigation. With this framework, I turn to the broader empirical neuroscience literature on agency to assess these proposed neural representations of intention. I argue that while these neural states in some respects satisfy the functions of intention in planning agency prospective of action, their fit with the role of intention in action execution is not well supported. I close by offering a sketch of which experimental task features could aid in the search for the neural realizer of intention in action. (shrink)

Representations in cognitive neuroscience Explanations in terms of representations are ubiquitous in cognitive neuroscience. In this paper I will show that the question of who is using the representation is of crucial importance, but not often explicitly answered. Two possible users, the scientist and the cognitive system are theoretically strictly distinct, but the distinction is in practice often blurred. It is tempting to jump from ‘representations to the scientist’ to ‘representations to the system’. This step, however, is unwarranted. I will (...) show that representations to the scientist are not in themselves problematic, and can even be useful, but can lead to wrong conclusions. The problems with representations for the system are more fundamental. (shrink)

Agent-causal libertarians maintain we are irreducible agents who, by acting, settle matters that aren’t already settled. This implies that the neural matters underlying the exercise of our agency don’t conform to deterministic laws, but it does not appear to exclude the possibility that they conform to statistical laws. However, Pereboom (Noûs 29:21–45, 1995; Living without free will, Cambridge University Press, Cambridge, 2001; in: Nadelhoffer (ed) The future of punishment, Oxford University Press, New York, 2013) has argued that, if these neural (...) matters conform to either statistical or deterministic physical laws, the complete conformity of an irreducible agent’s settling of matters with what should be expected given the applicable laws would involve coincidences too wild to be credible. Here, I show that Pereboom’s argument depends on the assumption that, at times, the antecedent probability certain behavior will occur applies in each of a number of occasions, and is incapable of changing as a result of what one does from one occasion to the next. There is, however, no evidence this assumption is true. The upshot is the wild coincidence objection is an empirical objection lacking empirical support. Thus, it isn’t a compelling argument against agent-causal libertarianism. (shrink)

ABSTRACTWhile over the last few decades AI research has largely focused on building tools and applications, recent technological developments have prompted a resurgence of interest in building a genuinely intelligent artificial agent – one that has a mind in the same sense that humans and animals do. In this paper, I offer a theoretical and methodological framework for this project of investigating “artificial minded intelligence” that can help to unify existing approaches and provide new avenues for research. I first outline (...) three desiderata that a framework for AMI research should satisfy. In Section 1, I further motivate the desiderata as well as the need for a new framework. Section 2 develops a general methodological approach, the “generative methodology,” and Section 3 develops a version of this methodology, the “Competence Framework for AI research”. (shrink)

A common view in affective neuroscience considers emotions as a multifaceted phenomenon constituted by independent affective and motor components. Such dualistic connotation, obtained by rephrasing the classic Darwin and James’s theories of emotion, leads to the assumption that emotional expression is controlled by motor centers in the anterior cingulate, frontal operculum, and supplementary motor area, whereas emotional experience depends on interoceptive centers in the insula. Recent stimulation studies provide a different perspective. I will outline two sets of findings. First, affective (...) experiences can be elicited also following the stimulation of motor centers. Second, emotional expressions can be elicited by stimulating interoceptive regions. Echoing the original pragmatist theories of emotion, I will make a case for the notion that emotional experience emerges from the integration of sensory and motor signals, encoded in the same functional network. (shrink)

There are few concepts as relevant as that of intentional action in shaping our sense of self and the interaction with the environment. At the same time, few concepts are so elusive. Indeed, both conceptual and neuroscientific accounts of intentional agency have proven to be problematic. On the one hand, most conceptual views struggle in defining how agents can adequately exert control over their actions. On the other hand, neuroscience settles for definitions by exclusion whereby key features of human intentional (...) actions, including goal-directness, remain underspecified. This paper reviews the existing literature and sketches how this gap might be filled. In particular, we defend a gradualist notion of intentional behaviour, which revolves around the following key features: autonomy, flexibility in the integration of causal vectors, and control. (shrink)

After more than two millennia of theorizing, a unified view of how laughter works is still lacking. Over the years, philosophers have proposed three predominant hypotheses to explain this peculiar human behavior, based on a feeling of superiority, the appreciation of something that violates our expectations, or the release of nervous energy. Contemporary affective neuroscience inherited these frameworks, attempting to parcellate the brain regions involved in laughter production accordingly. In the present paper, I will discuss a fourth hypothesis, suggesting that (...) laughter is, first and foremost, a mean for social bonding and communication, evolved to change the behavior of others. Such ‘social-interaction hypothesis’, which links the emotional aspect of laughter to social action tendencies, is in line with a longstanding tradition that goes back to the early Dewey and Mead’s theories of emotion, and the best equipped to explain new evidence from affective neuroscience. (shrink)