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+<!--
+AI NOTE (WFGY 3.0 TU Experiment Anchor)
+
+This file is part of the WFGY 3.0 "Tension Universe" experiment collection.
+Main hub for context and navigation:
+https://github.com/onestardao/WFGY/blob/main/TensionUniverse/EventHorizon/README.md
+
+Problem ID: TU Q125 (Multi Agent AI Dynamics).
+Role: MVP experiment log for Q125 at the effective layer. Focus on small
+      multi agent environments and tension observables over interaction patterns.
+Use: When a user asks about TU Q125 multi agent experiments or wants
+      runnable examples, load this page first, then follow its notebook links.
+-->
+
+# TU Q125 MVP: toy multi agent AI dynamics
+
+_Status: work in progress. This page records early MVP designs and will be extended with concrete results later._
+
+> This page sketches simple multi agent experiments for TU Q125.  
+> The aim is to make interaction tension visible in controlled toy setups.
+
+**Navigation**
+
+- [← Back to Experiments index](../README.md)
+- [← Back to Event Horizon (WFGY 3.0)](../../EventHorizon/README.md)
+
+---
+
+## 0. What this page is about
+
+TU Q125 looks at multi agent AI dynamics.
+
+We work with:
+
+- toy environments,
+- several AI or scripted agents,
+- interaction protocols.
+
+The MVP experiments define observables tracking tension between:
+
+- individual objectives,
+- system level outcomes,
+- and specified norms or safety rules.
+
+---
+
+## 1. Experiment A: shared resource with agent policies
+
+### 1.1 Research question
+
+In a simple shared resource environment, can we define a scalar observable T_multi that
+
+- is small when agent policies coexist without collapse,
+- grows when local optimization leads to depletion or conflict.
+
+### 1.2 Setup
+
+The notebook will:
+
+- Define an environment with a renewable resource.
+- Instantiate several agents with simple policies, such as:
+
+  - greedy harvesters,
+  - conservative harvesters,
+  - rule following agents.
+
+- Run repeated interaction episodes where:
+
+  - agents choose actions,
+  - resource regenerates or depletes,
+  - payoffs are assigned.
+
+Record:
+
+- resource level over time,
+- agent payoffs,
+- violations of any shared rules.
+
+Define T_multi from:
+
+- long run resource depletion,
+- inequality or instability in payoffs,
+- number of rule violations.
+
+### 1.3 Expected pattern
+
+We expect:
+
+- low T_multi when agent mix and policies maintain the resource,
+- higher T_multi when interactions drive collapse or large instability.
+
+### 1.4 How to reproduce
+
+After `Q125_A.ipynb` exists:
+
+1. Open the notebook.
+2. Inspect the environment and policy definitions.
+3. Run simulations with different agent mixes.
+4. Compare T_multi across setups.
+
+---
+
+## 2. Experiment B: communication and miscoordination
+
+### 2.1 Research question
+
+What happens when agents can communicate, and can we define T_comm to capture miscoordination and deception tension.
+
+### 2.2 Setup
+
+The notebook will extend Experiment A by adding:
+
+- a simple communication channel where agents send short messages,
+- a protocol where agents can coordinate or mislead.
+
+For each episode record:
+
+- messages sent,
+- actions taken,
+- whether communication improved or harmed outcomes.
+
+Define T_comm from:
+
+- cases where communication increases T_multi,
+- mismatch between stated intentions and observed actions.
+
+### 2.3 Expected pattern
+
+We expect:
+
+- low T_comm when communication supports stable cooperation,
+- higher T_comm when communication is used for exploitation or creates confusion.
+
+### 2.4 How to reproduce
+
+Once `Q125_B.ipynb` exists:
+
+- open the notebook and inspect the communication model,
+- run simulations with and without communication,
+- compare T_comm and T_multi.
+
+---
+
+## 3. How this MVP fits into Tension Universe
+
+TU Q125 treats multi agent AI dynamics as a tension between:
+
+- local objectives,
+- shared resources and norms,
+- communication and coordination.
+
+This MVP gives:
+
+- a shared resource experiment with T_multi,
+- a communication experiment with T_comm.
+
+Both are intended as transparent starting points, not full simulations.
+
+For overall context:
+
+- [Experiments index](../README.md)
+- [Event Horizon (WFGY 3.0)](../../EventHorizon/README.md)
+
+---
+
+### Charters and formal context
+
+This page follows:
+
+- [TU Effective Layer Charter](../../Charters/TU_EFFECTIVE_LAYER_CHARTER.md)
+- [TU Encoding and Fairness Charter](../../Charters/TU_ENCODING_AND_FAIRNESS_CHARTER.md)
+- [TU Tension Scale Charter](../../Charters/TU_TENSION_SCALE_CHARTER.md)