concept
active
concept:active-inference-curiosity-and-insight-friston-et-al-2017Active Inference, Curiosity and Insight (Friston et al., 2017)
The primary source paper being extracted
Neighborhood — ranked by edge-count
Thinkers (16)
thinker
- David Chalmersmentions
- Giovanni Pezzuloauthored
- Thomas MetzingermentionsPhilosopher of consciousness; opacity/transparency framework cited to explain meta-awareness mechanisms.
- Giulio TononimentionsDeveloper of integrated information theory; provides formal tools for measuring integration and consciousness in systems.
- Jakob Hohwymentions
- Karl J. Fristonauthored
- J. Allan Hobsonauthored
- Joshua B. Tenenbaummentions
- Christopher D. Frithauthored
- Marco Linauthored
- Sasha Ondobakaauthored
- Jürgen SchmidhubermentionsDeveloped theories of creativity, curiosity, and intrinsic motivation.
- BerlynementionsSeminal theorist of curiosity; two framing questions from Berlyne (1954) structure the paper's sections 3 and 4
- LeCun, Bengio & HintonmentionsAuthors of deep learning review in Nature 2015; contrasted with active inference approach
- Mark Jung-BeemanmentionsfMRI study author showing rSTG activation and gamma burst for verbal insight solutions
- Ullrich WagnermentionsAuthor of sleep inspires insight study showing doubled insight prevalence after nocturnal sleep
Frameworks (4)
framework
- Active InferenceintroducesFoundational framework by Karl Friston; the paper extends it to three hierarchical levels for modeling meta-awareness.
- Reinforcement LearningmentionsAlternative framework for agent behavior; based on reward maximization rather than free energy minimization.
- Progress Monitoring TheorymentionsPsychological theory of insight problem solving; enjoys empirical support from eye movement studies
- Representational Change TheorymentionsPsychological theory of insight; complemented by the normative active inference account
Methods (1)
method
- Abstract Rule Learning ParadigmintroducesExperimental simulation paradigm where agents learn a rule mapping central cue color to correct response location
Concepts (9)
concept
- Prior active inference paper providing detailed neurophysiological implementation of belief updates
- Companion paper to which readers are directed for detailed account of active inference scheme
- Deep LearningmentionsLearning hierarchical representations of non-decomposable functions; proposed as formal equivalent to ETI process.
- Choosing among candidate models based on model evidence.
- Source of fact-free learning concept; associated with insight and computational complexity reduction
- Eureka EffectmentionsPsychological phenomenon of sudden understanding; introduced by Auble et al. 1979; formalized here via BMR
- Source paper for Bayesian model reduction methodology used in structure learning
- Prior work linking sleep to free energy minimization; foundational for sleep-BMR analogy
- Shows variational and thermodynamic free energy share same minimum via Jarzynski equality
Questions (3)
question
- Empirical gap explicitly acknowledged; experiments reportedly in progress at time of writing
- How are model spaces constructed and explored in the absence of a full model (bottom-up structure learning)?associated_withResearch gap explicitly identified: the paper uses top-down BMR from a full model, avoiding this challenge
- Open question about inter-agent communication beyond model-space assumption
Venues (1)
venue
- Neural ComputationmentionsPublication venue for this paper.
Artifacts (1)
artifact
- Matlab code implementing active inference belief updates; available at fil.ion.ucl.ac.uk/spm/
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- §1, listing contributions.
- Friston et al. 2016: Active inference and learning (Neuroscience & Biobehavioral Reviews)concept0.829Foundational active inference reference
- §2, comment on expected free energy decomposition.
- Overall assessment from Discussion.
- Identifies an outstanding problem, Section 10.
- Abstract and §1, summarizing a key property.