Active Inference, homeostatic regulation and adaptive behavioural control.

TL;DR: This study proposes a physically-principled FE minimization theory overarching the essential features from both FEPs and reveals that the brain function of perception and behavioral control operates like Schr¨odinger’s clockwork and develops optimal trajectories in neural manifolds when the sensory perturbation is aroused.

TL;DR: In this paper , the teleonomic behavior of a collective intelligence composed of cells is studied and a lens is proposed to unify many phenomena across multiscale biology, and suggests a framework for understanding how teleonomic capacity increased and diversified during evolution.

TL;DR: Active Tree Search as mentioned in this paper combines the normative character and biological realism of a leading planning theory in neuroscience (Active Inference) and the scalability of Monte-Carlo methods in AI.

TL;DR: In this paper, the authors focus on the sensorimotor development of an infant child from gestation to toddler and discuss what aspects of the body, brain, and environment could allow for the sort of leaps of complexity observed in the developing infant that has heretofore not been replicable by artificial means.

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.