Solving the relevance problem with predictive processing
Bibliographic Data
| ID | 21591780 |
|---|---|
| Authors | Tom Darling (0000-0002-8533-7221, Monash University), Tom V Darling (Australian Regenerative Medicine Institute, corresponding author), Andrew W Corcoran (0000-0002-0449-4883, Monash University), Jakob Hohwy (0000-0003-3906-3060, Monash University) |
| Year | 2026 |
| Volume | 39 |
| Issue | 4 |
| Pages | 1472-1497 |
| Publication date | 2026-05-19 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Philosophical Psychology (JOURNAL) |
| Journal identifiers | ISSN: 0951-5089 • E-ISSN: 1465-394X |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/09515089.2025.2460502 |
| OpenAlex | W4407112782 |
| Language | EN |
| References cited | 79 |
The frame or relevance problem is a classic problem in cognitive science and philosophy. We attempt to resolve this problem by appealing to predictive processing, a growing theory of cognition. As such, it ought to explain one of the central processes of cognition, that is, how an agent context-sensitively determines relevance. Our solution begins by appealing to Bayesian prior probabilities, which intuitively reflect relevance for a predictive agent. However, prior probabilities are necessary but insufficient for solving the problem with predictive processing. We then turn to the broader predictive processing toolbox, leveraging the concepts of prediction, prediction error, and precision in order to explain relevance. This move reveals that the processes that optimize for prediction error minimization are crucial for realizing relevance. Although, they do not yet solve the entire problem, which also demands an agent select relevant actions, based on considerations about their consequences. By appealing to active inference, decision-making, and planning can be brought to bear on relevance, in addition to perceptual inference. With this final inclusion of action (as inference), we suggest predictive processing has the tools to comprehensively solve the problem of relevance
Cognitive psychology · Cognitive science · Epistemology · Political science · Action Observation and Synchronization · Computer Science · Embodied and Extended Cognition · Philosophy · Psychiatry, Mental Health, Neuroscience · Psychology
What computers still can't do
Surfing Uncertainty
The Mind Doesn't Work That Way
Active Inference
Reinforcement Learning
The free-energy principle
Active Inference, homeostatic regulation and adaptive behavioural control
Active inference and epistemic value
A theory of cortical responses
Active Inference
Bayesian surprise attracts human attention
Prospect Theory
Attention, Uncertainty, and Free-Energy
Predictive coding under the free-energy principle
The Markov blankets of life
Whatever next? Predictive brains, situated agents, and the future of cognitive science
The free-energy principle
The Modularity of Mind
The Predictive Mind
Conscious Self-Evidencing
Body as First Teacher
Predictive processing and relevance realization
Framing the predictive mind
Priors in perception
Predictions, precision, and agentive attention
The first prior
Surfing uncertainty
Active inference models do not contradict folk psychology
The anticipating brain is not a scientist
The frame problem, the relevance problem, and a package solution to both
Framing the frame problem
Happily entangled
Perception And Action
| Citation velocity | historical |
|---|---|
| Highly cited | No |