Results for "reasoning + action"
Combines value estimation (critic) with policy learning (actor).
Separates planning from execution in agent architectures.
RL using learned or known environment models.
Directly optimizing control policies.
Optimizing continuous action sequences.
Reward only given upon task completion.
Imagined future trajectories.
Control shared between human and agent.
Achieving task performance by providing a small number of examples inside the prompt without weight updates.
Constraining outputs to retrieved or provided sources, often with citation, to improve factual reliability.
Capabilities that appear only beyond certain model sizes.
Structured graph encoding facts as entity–relation–entity triples.
Enables external computation or lookup.
Software pipeline converting raw sensor data into structured representations.
Understanding objects exist when unseen.
Human-like understanding of physical behavior.
Mathematical guarantees of system behavior.
AI supporting legal research, drafting, and analysis.
Legal right to fair treatment.
Predicting case success probabilities.
AI proposing scientific hypotheses.
A system that perceives state, selects actions, and pursues goals—often combining LLM reasoning with tools and memory.
System-level design for general intelligence.