Results for "function calls"

Maximizing reward without fulfilling real goal.

Ensuring learned behavior matches intended objective.

Model behaves well during training but not deployment.

Willingness of system to accept correction or shutdown.

Asking model to review and improve output.

Applying learned patterns incorrectly.

Loss of old knowledge when learning new tasks.

Using output to adjust future inputs.

System returns to equilibrium after disturbance.

Learning physical parameters from data.

Predicts next state given current state and action.

Directly optimizing control policies.

Optimizing continuous action sequences.

Reward only given upon task completion.

Learning action mapping directly from demonstrations.

Sampling-based motion planner.

Optimal pathfinding algorithm.

Planning via artificial force fields.

Learning by minimizing prediction error.

Predicting protein 3D structure from sequence.

Predicting borrower default risk.

Agents optimize collective outcomes.

Tendency to gain control/resources.

Goals useful regardless of final objective.

Updating a pretrained model’s weights on task-specific data to improve performance or adapt style/behavior.