Multi-agent systems & Complex reasoning
Armağan Amcalar
Women Techmakers Berlin Generative AI Crash Course
October 28, 2024
WHO AM I?
AUTHORED ON GITHUB
Built with AI
Intelligence
dashersw
Adaptation to Environment
Reasoning and Problem-Solving
Learning and Memory
Skilled Use of Knowledge
AUTONOMOUS
dashersw
Acting independently or without human intervention
AGENT
dashersw
An entity that perceives its environment, makes decisions, and takes actions
COLLABORATION
dashersw
Multiple entities working together to achieve a common goal
multi-agent systems
dashersw
Operate independently
Interact with their environment
Communicate and cooperate with other agents
Learn and adapt based on their experiences
imitate intelligence with next-token prediction
dashersw
CAN YOU OR HOW DO YOU
HOW DOES ONE
CATCH A BALL?
dashersw
Visual Processing
Occipital lobe processes visual information.
Movement Planning
Parietal lobe and premotor cortex plan movement.
Execution of Movement
Primary motor cortex sends signals to muscles.
Coordination and Balance
Cerebellum ensures smooth movement.
Sensory Feedback
Somatosensory cortex adjusts grip.
https://training.seer.cancer.gov/module_anatomy/unit5_3_nerve_org1_cns.html
vectorized by Jkwchui, CC BY-SA 3.0, via Wikimedia Commons
EMERGENCE,
Emergent Behavior and Complex Systems
dashersw
Atoms form molecules, molecules form cells,
cells form organisms
each level exhibits new, emergent properties.
dashersw
dashersw
GESTALT
The whole is greater than the sum of its parts
dashersw
GESTALT
individual agents working together can achieve far more than they could separately.
coordinated actions lead to emergent behavior and intelligence.
dashersw
Multi-agent systems are networks of LLMs working together, each potentially specializing in different tasks or aspects of a problem
dashersw
- Division of cognitive labor
- Specialized expertise
- Parallel processing
- Enhanced reliability through cross-checking
dashersw
Why?
- Complex problem solving
- Scientific research assistance
- Business process automation
- Creative collaboration
dashersw
Some application areas
For autonomous behavior, ındıvıdual agents need to reason better.
dashersw
Popular reasonıng technıques
Chain of thought
Tree of thought
Graph of thought
dashersw
dashersw
Improving agent capabilities
Memory systems
Short-term memory
Long-term memory
Working memory
dashersw
Self-Reflection
Self-feedback loop for error analysis
Performance evaluation by confidence scoring
Strategy adjustment
dashersw
finally... Multi-agent SYstems
DELEGATION
Task planning and decomposition
Agent selection
Progress monitoring
Result integration
dashersw
Coordination patterns
Central coordinator (i.e. project manager)
Peer-to-peer network
Hierarchical network
Things to consider
Retry after errors
Fallback strategies
Exception reporting
dashersw
Types of Agents
- Expert agents (domain-specific knowledge)
- Critics (validation and verification)
- Coordinators (task management)
- Memory agents (information management)
dashersw
More advanced topics
dashersw
Memory, insights, habits
dashersw
what if questions
dashersw
what if English isn't the best language to prompt these agents?
dashersw
THANK YOU!
Armağan Amcalar
dashersw