Active Inference, homeostatic regulation and adaptive behavioural control.

TL;DR: A formal model that integrates cognitive and psychodynamic psychotherapeutic models of psychopathy is proposed to show how two major psychopathic traits called lacks remorse and self-aggrandizing can be understood as a form of abnormal Bayesian inference about the self.

TL;DR: This article proposes that brain architectures for predictive processing evolved gradually from simpler predictive loops in early ancestors, expanding in complexity through four main elaborations, aligning with evolutionary and comparative data on brain architectures in different species.

TL;DR: It is shown that fatigue levels can be incorporated in flexible cost-benefits computations that improve foraging efficiency and observed increased subcortical dopamine levels in fatigued mice: a marker of individual bias to use model-based control in humans.

TL;DR: Results reveal new and important mechanistic insights into the processes that may underlie problematic affect regulation in overweight populations.

TL;DR: It is proposed that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them, which provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task.

TL;DR: This paper presents and proves in detail a convergence theorem forQ-learning based on that outlined in Watkins (1989), showing that Q-learning converges to the optimum action-values with probability 1 so long as all actions are repeatedly sampled in all states and the action- values are represented discretely.

TL;DR: Findings in this work indicate that dopaminergic neurons in the primate whose fluctuating output apparently signals changes or errors in the predictions of future salient and rewarding events can be understood through quantitative theories of adaptive optimizing control.