Transforming De-Escalation with Agentic AI
In 2021, I wrote that storytelling games needed to leave “Sequential Logic” behind. At Axon, I built the engine that did it — creating AI agents that think, not just chat.
Why Traditional Training Failed
Law enforcement verbal skills training was stuck in the past, unable to teach the nuance of real human interaction.
Rigid Scripts
Traditional training relied on decision trees that couldn't adapt to the nuance of real conversations.
No Emotional Depth
Simulated subjects couldn't model the emotional progression that real de-escalation requires.
Limited Replayability
Officers could memorize the 'right' responses rather than learning adaptive communication.
“The most likely software architecture for new interactive storytelling games are neural networks and these are not explainable in the same manner that traditional sequential logic-based programs.”
— From my PhD dissertation, predicting the exact shift we implemented at Axon
How the Agents Think
A neuro-symbolic approach combining LLM creativity with rule-based reliability.
Neuro-Symbolic Processing
Pattern-Based Human Simulators
Moving from decision trees to dynamic, intent-based agents that adapt in real-time.
Agentic LLM Action Generator
Dynamic response generation that adapts to officer behavior in real-time, creating unique interactions every session.
Fuzzy Pattern Matching
Inspired by Valve's dialogue systems, matching officer intent against flexible patterns rather than exact phrases.
Humics Engine
Modeling emotional shifts, trust meters, and hidden 'agent facts' that drive realistic human behavior.
Neuro-Symbolic Architecture
Combining the creativity of LLMs with the reliability of rule-based systems for predictable yet dynamic agents.
AI That Tracks Emotional Progression
Officers must now adapt in real-time, learning true de-escalation skills.
Every conversation is unique
Agents respond to emotional cues
Deployed across law enforcement
Want to Dive Deeper?
Explore the academic foundation that predicted this technology shift.