Results for "collective agents"

Market reacting strategically to AI.

The text (and possibly other modalities) given to an LLM to condition its output behavior.

A high-priority instruction layer setting overarching behavior constraints for a chat model.

Continuous cycle of observation, reasoning, action, and feedback.

Expected cumulative reward from a state or state-action pair.

Separates planning from execution in agent architectures.

Learning from data generated by a different policy.

Models evaluating and improving their own outputs.

Using production outcomes to improve models.

Internal sensing of joint positions, velocities, and forces.

External sensing of surroundings (vision, audio, lidar).

Randomizing simulation parameters to improve real-world transfer.

Predicts next state given current state and action.

Directly optimizing control policies.

Modifying reward to accelerate learning.

Reward only given upon task completion.

Modeling environment evolution in latent space.

Imagined future trajectories.

Acting to minimize surprise or free energy.

Perceived actions an environment allows.

Human-like understanding of physical behavior.

Humans assist or override autonomous behavior.

Intelligence emerges from interaction with the physical world.

Robots learning via exploration and growth.

Learning without catastrophic forgetting.

Combination of cooperation and competition.

No agent benefits from unilateral deviation.

Rules governing auctions.

Designing efficient marketplaces.

Existential risk from AI systems.