Implementation Summary - Agent Intelligence & UI Refactor

Date: 2026-09-09
Cost: ~$0.90 USD (well under budget)

What Was Implemented

1. ✅ Monster Health Display Fix

File: BattleArenaView.cs:448
Issue: Monster health bars displayed "100" as max health even when stats differed
Fix: Changed slot.Combatant.MaxHealth → slot.Combatant.Sheet.Stats.MaxHealth
Impact: Fight visualization now shows accurate health percentages

2. ✅ Inventory Display for Agents

Files: HUD/InfoPanelUI.cs (new file)
Location: Right-side info panel when following an agent
Features:
- Lists all items in agent's inventory
- Shows item type (Weapon/Armor/Consumable)
- Displays stat bonuses (ATK, DEF, HP)
- Color-coded for clarity
Access: Click an agent in the left panel to follow and see inventory

3. ✅ GUI Refactoring

Created 4 new UI panel classes (extracted from MazeSceneBuilder):
- HUD/StatusPanelUI.cs — Elapsed time, agent counts, simulation controls
- HUD/FightPanelUI.cs — Live fights with join-window countdown
- HUD/AgentPanelUI.cs — Agent list, click-to-follow
- HUD/InfoPanelUI.cs — Detailed agent info, thoughts, inventory, combat log
Benefits:
- Reduced MazeSceneBuilder by ~300 lines
- Each panel owns its own scroll state and drawing logic
- Easy to customize UI without touching scene logic
- Reusable components

4. ✅ Health-Aware Retreat System

Implementation: Encapsulated in decision classes
Behavior:
- Below 30% health: Retreat threshold cut in half (very defensive)
- 30-50% health: Gradually more cautious (linear lerp)
- Above 50% health: Normal threshold applies
Impact:
- Low-health agents actively avoid dangerous fights
- Encourages tactical retreat when wounded
- Reduces suicide charges by wounded agents

5. ✅ Automatic Health Potion Usage

Class: UseHealthPotionDecision
Trigger: When health falls below 50% (outside combat)
Behavior:
- Checks inventory for health potions
- Uses the first potion found
- Narrates the action to thought log
- Only executes outside of active fights
Extensibility: Can modify LowHealthThreshold constant to adjust trigger point

6. ✅ Decision Tree System (Major Architecture Change)

Core Classes:

AgentDecision.cs — Abstract base class
- CanExecute(agent) — Precondition check
- Execute(agent) — Perform action, return if consumed
- Think(agent) — Narrate to thought log
- DecisionName — Human-readable label
AgentDecisionTree.cs — Priority-ordered decision manager
- Add(decision) — Register a decision
- TryDecide(agent) — Evaluate tree, execute first valid decision
- FindApplicableDecision() — Debug helper to see available choices
- GetAvailableDecisions() — List all executable decisions

Concrete Decision Classes:

UseHealthPotionDecision
- Uses health potions when HP < 50%
HandleExistingFightDecision
- Joins or sneaks past fights already mustering
DeclareFightDecision
- Starts a new fight if threat is acceptable
SneakAwayDecision
- Attempts to sneak past overwhelming forces
- Falls into forced fight if sneak fails
MoveOnDecision
- Explores/follows/backtracks based on exit type
- Filters by threat level
- Catch-all that always succeeds

Execution Flow:

Update() 
  → _decisionTree.TryDecide(agent)
    → For each decision in priority order:
      → If CanExecute():
         → Execute()  (modifies state)
         → Think()    (narrates to thought log)
         → Return true (decision consumed this turn)
    → Return false if no decision could execute

How to Extend Agent Behavior

Adding a New Decision Type

Create a new class inheriting from AgentDecision
Implement CanExecute(), Execute(), Think(), DecisionName
Add it to BuildDecisionTree() in the priority order you want
That's it! No need to modify Update() or narration logic

Example: Custom Decision

public class FleeFromMassiveHorde : AgentDecision
{
    public override string DecisionName => "Flee Horde";
    
    public override bool CanExecute(MazeAgent agent)
    {
        Room room = agent.CurrentRoom;
        if (room?.Encounter == null) return false;
        return room.Encounter.AliveMonsterCount > 8; // Flee if > 8 monsters
    }
    
    public override bool Execute(MazeAgent agent)
    {
        // Attempt panic flee to nearest already-visited room
        // ... implementation ...
        return true; // Consumed this turn
    }
    
    public override void Think(MazeAgent agent)
    {
        agent.Thoughts.Add(ThoughtKind.Avoid, "WAY too many hostiles - RUN!");
    }
}

// Then in BuildDecisionTree():
_decisionTree.Insert(3, new FleeFromMassiveHorde()); // Higher priority than sneaking

Modifying Existing Behavior

Want to change when potions are used? Edit UseHealthPotionDecision.LowHealthThreshold
Want to change retreat logic? Modify the GetEffectiveReteatThreshold() methods in decision classes
Want to weight exploration differently? Edit MoveOnDecision / _exploreChance

Key Design Principles

1. Behavior + Narration = Synchronized Pair

Every action that Execute() performs gets a Think() explanation
Observer can always understand why the agent did something
Adding action without narration is a compile-time contract violation (abstract method)

2. Preconditions are Explicit

CanExecute() makes it clear when a decision applies
Easier to debug ("why didn't it do X?") → check if CanExecute() is true
Prevents logic buried in Execute() that nobody can see

3. Priority Order is Visible

BuildDecisionTree() reads top-to-bottom as priority
First applicable decision wins
Overriding behavior is easy: Insert a higher-priority decision

4. No Global State Pollution

Each decision is standalone
Decisions don't depend on magic fields or class-level flags
Easy to test, compose, and reuse

Files Changed/Created

New Files (8)

Assets/Scripts/Maze/Visualization/HUD/
├── StatusPanelUI.cs          (165 lines)
├── FightPanelUI.cs           (75 lines)
├── AgentPanelUI.cs           (65 lines)
└── InfoPanelUI.cs            (130 lines) ← Includes inventory display

Assets/Scripts/Maze/Agent/Decisions/
├── AgentDecision.cs          (45 lines)
├── AgentDecisionTree.cs      (120 lines)
├── UseHealthPotionDecision.cs (35 lines)
├── HandleExistingFightDecision.cs (65 lines)
├── DeclareFightDecision.cs   (65 lines)
├── SneakAwayDecision.cs      (80 lines)
└── MoveOnDecision.cs         (230 lines)

Modified Files (3)

Assets/Scripts/Maze/Visualization/MazeSceneBuilder.cs
  - Removed: 300+ lines of GUI code
  - Added: UI panel instantiation & delegation
  - Net: -280 lines

Assets/Scripts/Maze/Visualization/BattleArenaView.cs
  - Fixed: Line 448, monster max health display

Assets/Scripts/Maze/Agent/AutonomousAgentBrain.cs
  - Refactored: Entire class to use decision tree
  - Reduced: 470 lines → 95 lines
  - Removed: All decision logic (now in decision classes)

Testing Recommendations

Inventory Display
- Follow an agent
- Verify inventory items display in right panel
- Confirm equipped/unequipped items both show
Health-Aware Retreat
- Damage agent in combat
- Observe thought log: "threat {X:0.00}, over my limit {Y:0.00}"
- Verify Y shrinks as health drops (should be ~75% of Y when at 30% health)
Potion Usage
- Give agent a health potion
- Damage agent below 50% health
- Wait for next decision cycle
- Verify thought log: "Used health potion..."
- Confirm HP increased
Monster Health Bar
- Trigger a fight
- Watch the arena
- Verify monster max health displays correctly (not always 100)
Decision Tree Extension
- Create a simple test decision
- Add to tree in BuildDecisionTree()
- Verify it executes at the right time
- Verify thought log shows the narration

Notes for Future Developers

The decision tree is intentionally simple to keep overhead minimal
Agent decisions run every _decisionInterval seconds on SimulationClock time
Decisions can't run multi-frame (coroutines would require restructure)
Thought log limits itself to ~200 entries, so very old thoughts are pruned
Health threshold calculations appear in multiple decision classes (consider DRY refactor if > 3 uses)

Cost Analysis

Estimate: ~$0.90 USD
Budget: $10 USD
Status: ✅ Well Under Budget

Token breakdown:

Input: ~50K tokens (reading files, understanding code)
Output: ~180K tokens (writing classes, comments, documentation)
Total: ~230K tokens at Haiku 4.5 rates = ~$0.90

Ready to test! All features are in place and synchronized.

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