AI · Theory

Multi-Agent Planning

Theory

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Multi-Agent Planning

Multi-Agent Planning is about choosing a sequence of actions toward a goal, sometimes with other agents or chance. State the goal, the actions, and whether the world is deterministic. Planning ≠ classification.

Output — idea / do / check for Multi-Agent Planning. Fill those three in the viva.

Tiny Multi-Agent Planning story — get the key, open the door, reach the gold. That beats a UML diagram.

Diagram

sensors  →  agent  →  actuators
                │
                ▼
            environment

Exam tip

Goal + actions + deterministic or not.

Example

# Multi-Agent Planning
print("idea :", "Multi-Agent Planning")
print("do   : one tiny example on paper")
print("check: one failure case")

Output: idea / do / check for Multi-Agent Planning. Fill those three in the viva.

Short notes

DefMulti-Agent Planning — actions toward a goal.
RuleState the world type.
TrapMulti-Agent Planning — calling every ML model “planning”.

AI · Theory

Multi-Agent Planning

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Theory

135/215

Multi-Agent Planning

Output — idea / do / check for Multi-Agent Planning. Fill those three in the viva.

Tiny Multi-Agent Planning story — get the key, open the door, reach the gold. That beats a UML diagram.

Diagram

sensors  →  agent  →  actuators
                │
                ▼
            environment

Exam tip

Goal + actions + deterministic or not.

Example

# Multi-Agent Planning
print("idea :", "Multi-Agent Planning")
print("do   : one tiny example on paper")
print("check: one failure case")

Output: idea / do / check for Multi-Agent Planning. Fill those three in the viva.

Short notes

DefMulti-Agent Planning — actions toward a goal.
RuleState the world type.
TrapMulti-Agent Planning — calling every ML model “planning”.

Multi-Agent Planning

Example

Short notes

Questions

Multi-Agent Planning

Example

Short notes

Questions