🎯 Agent Planning Strategies

Master multi-step reasoning and task decomposition for AI agents

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Memory Systems

Introduction to Planning

🎯 Why Planning Matters

Planning enables AI agents to tackle complex, multi-step problems by decomposing goals into manageable subtasks. Instead of reacting to immediate inputs, planning agents reason about future states, consider alternatives, and create structured action sequences.

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Key Insight

Effective planning combines forward reasoning (what steps lead to the goal) with backward reasoning (what's needed to reach each step), enabling agents to solve problems that require coordinated multi-step actions.

🔄 The Planning Loop

1
Goal Setting

Define clear objectives and success criteria

2
Decomposition

Break down complex goals into smaller subgoals

3
Action Selection

Choose specific actions to achieve each subgoal

4
Execution & Monitoring

Execute plan and adapt based on results

🤖
Autonomous Agents

Self-directed task completion without human intervention

🎮
Game AI

Strategic planning for complex game scenarios

🏭
Workflow Automation

Multi-step business process orchestration

✅ Benefits

  • Solve complex multi-step problems
  • Optimize for long-term outcomes
  • Handle uncertainty and adapt
  • Transparent reasoning process

⚠️ Challenges

  • Computational complexity
  • Plan execution failures
  • Dynamic environment changes
  • Balancing depth vs speed