THE GATE BATTLE: UNLOCKING HUMAN INSTINCTS
The Gate Battle is not just a test—it is the first training ground for every aspiring warrior.
The Gate Battle is not just a test—it is the first training ground for every aspiring warrior. Most traders have dormant instincts—TradeTant’s goal is to awaken them and forge unshakable trust in their own decision-making. This is where peasants become warriors.
2.1. Structure: 5 Stages, 5 Timeframes Each
To prove their worth, warriors must fight AI in 25 battles across 5 progressive stages (sessions). Each stage consists of 5 timeframes, where traders must predict price movements across increasing difficulty levels.
The progressive stacking of chart details ensures that warriors develop their ability to instinctively understand patterns, starting with simple visualizations and advancing to complex market data.
Stage-by-Stage Breakdown
Each stage introduces new layers of complexity, simulating real-world trading conditions while progressively challenging the warrior’s instincts and decision-making skills.
Stage 1: Average Price Line
Chart Type: A single line representing the average price movement over time.
Objective: Predict the next price movement based solely on the trend of the average price line.
AI Assistance: None. Warriors rely purely on their instincts.
Skills Trained: Basic pattern recognition and trend identification.
Stage 2: Average Price Line + Volume Blocks
Chart Type: The average price line is now accompanied by volume blocks that indicate trading activity.
Objective: Incorporate volume data into predictions, identifying whether high or low volume correlates with price changes.
AI Assistance: The first AI Piece (earned in Stage 1) provides a suggested prediction line that can be adjusted by the warrior.
Skills Trained: Understanding the relationship between price and volume, refining intuition for market momentum.
Stage 3: Average Price Line + Volume Blocks + Candlesticks
Chart Type: Adds candlestick charts to the previous elements, showing open, close, high, and low prices for each timeframe.
Objective: Predict price movements using candlestick patterns, volume, and the average price line.
AI Assistance: The second AI Piece (earned in Stage 2) enhances the suggested prediction line, incorporating candlestick analysis.
Skills Trained: Reading candlestick patterns, combining multiple data points for more accurate predictions.
Stage 4: Full Candlestick Chart + Volume + Indicators
Chart Type: Includes all previous elements, plus technical indicators such as moving averages, RSI, and MACD.
Objective: Use technical indicators alongside candlestick patterns and volume to predict price movements.
AI Assistance: The third AI Piece (earned in Stage 3) integrates indicator-based predictions, offering a more sophisticated analysis.
Skills Trained: Interpreting technical indicators, developing a holistic view of market conditions.
Stage 5: Full Chaos Trading
Chart Type: Simulates real-world market volatility, including sudden spikes, dips, and erratic price movements.
Objective: Adapt to unpredictable market conditions, relying on instincts honed in earlier stages.
AI Assistance: The fourth AI Piece (earned in Stage 4) provides dynamic, real-time predictions, but warriors must decide when to trust the AI and when to override it.
Skills Trained: Decision-making under pressure, balancing human intuition with AI-driven insights.
2.2. How Each Battle Works
Interaction: The user clicks on the chart to draw their predicted price curve for the next timeframe.
AI Bot Prediction: The AI Bot simultaneously generates its own prediction, which is compared against the user’s input.
Tolerance Measurement: A +/- 5% tolerance is applied, measuring closeness to reality.
If both the user and AI are out of range for the majority of the intervals, the set is replayed.
Winning a battle improves the user’s final score for that stage.
Losing a stage (total score for the 5 timeframes) removes 1 life.
If they tie, they play again the set in which their scores were closest.
Live Market Feed: Each battle starts when the user interacts with a live market feed, ensuring real-world unpredictability.
Consequences of Failure:
If a warrior loses all 5 lives, their deposit is unlocked for withdrawal.
If the user withdraws their deposit, any progress (stages won) will also be deleted.
2.3. Capturing AI & Building the AI Suit
Each AI Bot defeated becomes a part of the user’s AI Suit, granting new abilities and strategic advantages in the next battles.
AI Suit Evolution Through Training
The AI Suit is not just a static tool—it evolves dynamically based on the warrior’s performance and decisions during the Gate Battle.
AI Piece Mechanics
Training Data: Each AI Piece is trained on the warrior’s battle data, including successful predictions, failed attempts, and adjustments made to AI suggestions.
Skill Integration: As warriors progress through stages, the AI Suit learns to integrate new skills:
Stage 1 AI Piece: Focuses on basic trend identification.
Stage 2 AI Piece: Adds volume analysis capabilities.
Stage 3 AI Piece: Incorporates candlestick pattern recognition.
Stage 4 AI Piece: Introduces indicator-based predictions.
Stage 5 AI Piece: Specializes in adaptive decision-making under chaotic conditions.
Synergistic Learning Effect
The AI Suit’s evolution creates a synergetic learning effect, teaching warriors:
What abilities the AI Suit offers.
When to trust the AI Suit and when to rely on instincts.
How to combine their own intuition with AI-driven decisions.
Stage Cleared
AI Suit Power Unlocked
Skills Enhanced
Stage 1
AI-assisted Market Awareness
Trend identification
Stage 2
Pattern Recognition Augment
Volume analysis
Stage 3
Price Action Precision
Candlestick patterns
Stage 4
AI-Integrated Decision Support
Indicator-based predictions
Stage 5
Fully Functional AI Suit
Adaptive decision-making
2.4. Technical Details of AI Training
The AI Suit’s training process is designed to mirror the warrior’s progression through the Gate Battle, ensuring that the AI evolves in tandem with the user’s skills.
Training Workflow
Data Collection:
Each battle generates data on the warrior’s predictions, AI suggestions, and actual market outcomes.
This data is used to train the corresponding AI Piece.
Model Architecture: (Initial suggestions, subject to change)
Stage 1 AI Piece: Simple linear regression model for trend identification.
Stage 2 AI Piece: Recurrent Neural Network (RNN) for volume analysis.
Stage 3 AI Piece: Convolutional Neural Network (CNN) for candlestick pattern recognition.
Stage 4 AI Piece: Hybrid model combining CNNs and Long Short-Term Memory (LSTM) networks for indicator-based predictions.
Stage 5 AI Piece: Reinforcement Learning (RL) model for adaptive decision-making.
Feedback Loop:
The AI Suit continuously learns from the warrior’s decisions, adjusting its predictions to align with the user’s evolving strategy.
Integration:
Once all five AI Pieces are earned, they are integrated into a unified AI Suit, capable of handling complex, real-world trading scenarios.
2.5. Outcomes of the Gate Battle
By Stage 5, warriors are no longer just traders—they have trained AI as an extension of themselves. This AI Suit will define their journey inside the AI Arena, equipping them with the tools needed to conquer real-world markets.
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