Armağan Amcalar PRO
Armagan is the founder of Coyotiv GmbH, and is currently on a mission to bring a scalable and nimble engineering culture to startups and enterprises. Armagan is a public speaker, a mentor and a lecturer.
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
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Adaptation to Environment
Reasoning and Problem-Solving
Learning and Memory
Skilled Use of Knowledge
AUTONOMOUS
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Acting independently or without human intervention
AGENT
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An entity that perceives its environment, makes decisions, and takes actions
COLLABORATION
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Multiple entities working together to achieve a common goal
multi-agent systems
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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
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CAN YOU OR HOW DO YOU
HOW DOES ONE
CATCH A BALL?
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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
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Atoms form molecules, molecules form cells,
cells form organisms
each level exhibits new, emergent properties.
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GESTALT
The whole is greater than the sum of its parts
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GESTALT
individual agents working together can achieve far more than they could separately.
coordinated actions lead to emergent behavior and intelligence.
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Multi-agent systems are networks of LLMs working together, each potentially specializing in different tasks or aspects of a problem
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- Division of cognitive labor
- Specialized expertise
- Parallel processing
- Enhanced reliability through cross-checking
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Why?
- Complex problem solving
- Scientific research assistance
- Business process automation
- Creative collaboration
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Some application areas
For autonomous behavior, ındıvıdual agents need to reason better.
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Popular reasonıng technıques
Chain of thought
Tree of thought
Graph of thought
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Improving agent capabilities
Memory systems
Short-term memory
Long-term memory
Working memory
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Self-Reflection
Self-feedback loop for error analysis
Performance evaluation by confidence scoring
Strategy adjustment
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finally... Multi-agent SYstems
DELEGATION
Task planning and decomposition
Agent selection
Progress monitoring
Result integration
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Coordination patterns
Central coordinator (i.e. project manager)
Peer-to-peer network
Hierarchical network
Things to consider
Retry after errors
Fallback strategies
Exception reporting
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Types of Agents
- Expert agents (domain-specific knowledge)
- Critics (validation and verification)
- Coordinators (task management)
- Memory agents (information management)
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More advanced topics
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Memory, insights, habits
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what if questions
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what if English isn't the best language to prompt these agents?
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THANK YOU!
Armağan Amcalar
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Multi-agent systems & complex reasoning
By Armağan Amcalar
Multi-agent systems & complex reasoning
Explore the fascinating interplay between multi-agent systems, human learning, and the evolution of society. Discover how artificial general intelligence emerges from complex reasoning and the role of large language models in shaping our understanding of intelligence.
