Active Inference, homeostatic regulation and adaptive behavioural control.

TL;DR: In this paper , the Free Energy Principle and Active Inference (FEP-AI) framework is used to simulate the reciprocal message passing performed by mammalian nervous systems, allowing for the flexible construction of representations of self-world dynamics with varying degrees of temporal depth.

TL;DR: In this article , the role of the medial prefrontal cortex (mPFC) in foraging behavior was investigated on mice using foraging tasks that required integration of past oro-sensory rewards and past choices, and the mPFC selectively represents sensorimotor events, which organize into a spatiotemporal map encoding location and temporal delay of past rewards and choices relative to the animal's current epoch in time.

TL;DR: In this paper , the authors suggest that moral motivation can be explained by domain-general aspects of brain-body interactions, in combination with incentives to regulate local and global social environments.

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.