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# Objectives

<p align="center">
  <strong>Turn intent into measurable action.</strong>
</p>

<p align="center">
  <img src="https://img.shields.io/badge/Goals-2563EB?style=for-the-badge" alt="Goals">
  <img src="https://img.shields.io/badge/Planning-7C3AED?style=for-the-badge" alt="Planning">
  <img src="https://img.shields.io/badge/Optimization-14B8A6?style=for-the-badge" alt="Optimization">
  <img src="https://img.shields.io/badge/Evaluation-F59E0B?style=for-the-badge" alt="Evaluation">
</p>

---

## Intelligence needs objectives

**Objectives** is an independent Hugging Face organization focused on how AI systems represent, prioritize, optimize, evaluate, and revise goals.

A capable system can generate actions.

A useful system should also understand:

> **What are we trying to achieve?**

---

# The Objective Loop

```text
INTENT
  ↓
OBJECTIVE
  ↓
CONSTRAINTS
  ↓
PLAN
  ↓
ACTION
  ↓
MEASUREMENT
  ↓
UPDATE
```

Objectives connect **intent** with **behavior**.

---

## Goal Representation

How should an AI system represent what it is trying to accomplish?

Possible topics:

- explicit goals
- subgoals
- success criteria
- priorities
- deadlines
- constraints
- preferences
- stop conditions

---

## Multi-Objective Optimization

Real tasks often involve competing goals.

For example:

```text
maximize quality
minimize cost
reduce latency
preserve safety
respect constraints
```

There may be no single perfect answer.

A system may need to reason about trade-offs.

---

## Planning

Objectives become useful when they guide action.

```text
GOAL
 ↓
SUBGOALS
 ↓
PLAN
 ↓
EXECUTION
 ↓
CHECK
```

Possible research areas:

- decomposition
- sequencing
- prioritization
- replanning
- resource allocation
- long-horizon planning

---

## Success Criteria

A goal without a measurable outcome is difficult to evaluate.

Possible questions:

- What counts as success?
- What counts as partial success?
- When should the system stop?
- Which metrics matter?
- How should trade-offs be scored?

---

## Objective Conflicts

AI systems may receive goals that conflict.

Example:

```text
Objective A: maximize accuracy
Objective B: minimize latency
Objective C: minimize cost
```

A useful system should make these conflicts visible rather than hide them.

---

## Objective Updates

Goals can change during execution.

```text
OLD OBJECTIVE
      ↓
AUTHORIZED UPDATE
      ↓
NEW OBJECTIVE
      ↓
REPLAN
```

This connects Objectives naturally with agents, orchestration, corrigibility, evaluation, and planning.

---

# Possible Spaces

### Objective Builder
Turn a broad intention into structured goals, constraints, and success criteria.

### Multi-Objective Planner
Compare plans across quality, cost, time, and risk.

### Goal Decomposer
Break one high-level objective into measurable subgoals.

### Objective Conflict Detector
Identify competing or contradictory goals.

### Success Criteria Designer
Convert vague objectives into measurable evaluation criteria.

### Goal Update Simulator
Test how a plan changes when an objective changes.

### Pareto Explorer
Visualize trade-offs between multiple objectives.

### Agent Objective Inspector
Inspect goals, priorities, constraints, and stop conditions of an agent workflow.

---

# Possible Datasets

Potential datasets may include:

```text
goal-decomposition-tasks
multi-objective-scenarios
objective-conflicts
success-criteria-examples
agent-goal-traces
planning-objectives
goal-update-cases
```

Useful fields may include:

- objective
- priority
- constraint
- metric
- target
- subgoal
- tradeoff
- outcome
- success

---

# Possible Models

Models may support:

- goal extraction
- objective classification
- subgoal generation
- priority ranking
- conflict detection
- success-criteria generation
- plan scoring
- multi-objective selection

---

# A Simple Objective Record

```json
{
  "objective": "Reduce inference cost",
  "constraints": [
    "quality must remain above threshold",
    "latency must stay below 2 seconds"
  ],
  "metrics": [
    "cost_per_request",
    "quality_score",
    "latency_ms"
  ],
  "success": "20% lower cost without violating constraints"
}
```

Clear objectives make evaluation easier.

---

# Objectives + Agents

Agents need goals.

A robust agent may need more than a sentence describing a task. It may need:

```text
goal
+
priority
+
constraints
+
success criteria
+
stop conditions
```

That structure can make behavior easier to inspect and evaluate.

---

# Objectives + World Models

World models may simulate possible futures.

Objectives determine which futures are desirable.

```text
WORLD MODEL
    ↓
POSSIBLE FUTURES
    ↓
OBJECTIVE FUNCTION
    ↓
SELECTED PLAN
```

Prediction tells us what might happen.

Objectives help decide what should happen.

---

# Objectives + Corrigibility

Objectives should not become permanently fixed.

Authorized users may need to change, narrow, replace, cancel, or constrain them.

A well-designed AI system should remain responsive to legitimate objective updates.

---

# Objectives + Evaluation

Evaluation asks whether a system performed well.

Objectives define what **well** means.

Without a clear objective, a score can be meaningless.

---

# Design Principles

### Make goals explicit
Hidden objectives are difficult to inspect.

### Separate goals from constraints
What we want and what we must not violate are different.

### Define success
Every important objective should have measurable criteria where possible.

### Expose trade-offs
Competing goals should be visible.

### Allow updates
Objectives may change.

### Evaluate outcomes
Intent matters, but results matter too.

---

# Who Is Objectives For?

Objectives may be useful for:

- agent developers
- AI researchers
- planning systems
- orchestration teams
- optimization researchers
- evaluation teams
- robotics developers
- enterprise AI builders
- open-source contributors

---

# Long-Term View

As AI systems become more capable, the difficult question may increasingly shift from:

> **What can the system do?**

to:

> **What should the system optimize for?**

More intelligence makes objective design more important, not less.

---

# Independent Organization

**Objectives is an independent Hugging Face community organization.**

It is not an official optimization platform, standards body, model provider, research institute, or Hugging Face organization.

The name **Objectives** reflects the central idea:

> **define what matters, make trade-offs explicit, and connect goals to measurable outcomes.**

---

<p align="center">

# OBJECTIVES

### **Align. Plan. Measure. Improve.**

</p>