concept
active
concept:artificial-agentsArtificial agents
Synthetic agents (here RL-trained neural networks) whose causal emergence was previously largely unknown; the paper addresses this gap.
Neighborhood — ranked by edge-count
Papers (1)
paper
Concepts (2)
concept
- Neural-network agentsassociated_withThe artificial agents trained with RL in this study, whose latent dynamics are analyzed for causal emergence.
- Biological agentsassociated_withNatural living systems that have been shown to increase causal emergence after learning, motivating the cross-domain comparison.
Questions (1)
question
- Core motivating question addressed by the empirical RL study; identified as major knowledge gap.
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.
- Any autonomous system including living and non-living forms that embodies a perception-action cycle and tries to navigate and persist in an environment
- Computational modeling approach studying living/cognitive systems; used to test hypotheses about self-illusion effects without direct intervention.
- Domain where consciousness theories are being applied to synthetic systems; part of broader context of unconventional embodiments.
- Higher-level systems built on top of LLMs that produce and consume representations beyond next-token prediction; proposed as potential candidates for consciousness.
- CIMC research direction studying how AI systems develop internal models, form self-representations, and construct coherent personalities from language modeling
- Higher-level individuals (e.g., embryo, swarm) that arise from cooperative subunits, possessing goals not assignable to any one component.
- Methods that use agentic reasoning; incur context-switching latency from external execution.
- Capacity for autonomous action; requires formal definition linking to selfhood, control, and sense of agency.