activity
20212025
most citedExploration and preference satisfaction trade-off in reward-free learning

11 citations · 15 across the 6 of their papers we have counts for

collaborators

8 papers

eess.SY2025

EcoNet: Multiagent Planning and Control Of Household Energy Resources Using Active Inference

John C. Boik, Kobus Esterhuysen, Jacqueline B. Hynes +5

Advances in automated systems afford new opportunities for intelligent management of energy at household, local area, and utility scales. Home Energy Management Systems (HEMS) can…

q-bio.NC20222 cited

Predictive coding and stochastic resonance as fundamental principles of auditory perception

Achim Schilling, William Sedley, Richard Gerum +7

How is information processed in the brain during perception? Mechanistic insight is achieved only when experiments are employed to test formal or computational models. In analogy t…

cs.RO20222 cited

Reclaiming saliency: rhythmic precision-modulated action and perception

Ajith Anil Meera, Filip Novicky, Thomas Parr +3

Computational models of visual attention in artificial intelligence and robotics have been inspired by the concept of a saliency map. These models account for the mutual informatio…

stat.ML2021

Active inference, Bayesian optimal design, and expected utility

Noor Sajid, Lancelot Da Costa, Thomas Parr +1

Active inference, a corollary of the free energy principle, is a formal way of describing the behavior of certain kinds of random dynamical systems that have the appearance of sent…

cs.AI202111 cited

Exploration and preference satisfaction trade-off in reward-free learning

Noor Sajid, Panagiotis Tigas, Alexey Zakharov +2

Biological agents have meaningful interactions with their environment despite the absence of immediate reward signals. In such instances, the agent can learn preferred modes of beh…

q-bio.NC2021

Bayesian brains and the Rényi divergence

Noor Sajid, Francesco Faccio, Lancelot Da Costa +3

Under the Bayesian brain hypothesis, behavioural variations can be attributed to different priors over generative model parameters. This provides a formal explanation for why indiv…