AI MONSTER
  • AI MONSTER ($AIMON) Overview
  • AI-Generated Monsters: Technical Core (DeepSeek & Generative AI)
    • 2.1 Monster Design AI Architecture
    • 2.2 Reinforcement Learning with Human Feedback (RLHF)
    • 2.3 Multi-modal AI Training Framework
    • 2.4 FLUX Integration
    • 2.5 NFT Integration for AI Monsters
    • 2.5 Advanced NFT Minting Process
    • 2.6 Upgrading and Evolution Mechanisms
    • 2.7 GameFi and Film Production Integration
  • Solana & $AIMON Token Economy
    • 3.1 Why Solana?
    • 3.2 $AIMON Token Utility
  • AI MONSTER Use Cases
    • 4.1 Gaming & GameFi
      • 4.1.1 AI-Generated Game Entities
      • 4.1.2 Monster Training and Personalization
      • 4.1.3 Play-to-Earn (P2E) Mechanics
      • 4.1.4 AI Evolution System
    • 4.2 Film & Animation
      • 4.2.1 High-Quality CG Monster Generation
      • 4.2.2 AI-Driven Simulations for Enhanced Visual Effects
      • 4.2.3 Dynamic Scene Generation and Integration
      • 4.2.4 Workflow Integration and Production Efficiency
  • Roadmap & Future Plans
    • 5.1 Q1 - Q2 2025
    • 5.2 Q3 - Q4 2025
    • 5.3 Long-Term Vision (2026 & Beyond)
  • Join the AI MONSTER Ecosystem
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  1. AI MONSTER Use Cases
  2. 4.1 Gaming & GameFi

4.1.3 Play-to-Earn (P2E) Mechanics

AI MONSTER implements a robust P2E model that rewards players for various activities:

  1. Combat Rewards

  2. Earn tokens for defeating AI monsters or other players

  3. Bonus rewards for exceptional performance or defeating rare monsters

  4. Capture and Training

  5. Rewards for successfully capturing wild AI monsters

  6. Incentives for training and evolving monsters to higher levels

  7. Trading and Marketplace

  8. Earn commissions from monster trades in the marketplace

  9. Rewards for providing liquidity to trading pools

  10. Content Creation

  11. Incentives for creating popular monster designs

  12. Rewards for contributing to the AI training data

Example: P2E Reward Distribution

class P2ERewardSystem {
  constructor(player, actionType, actionData) {
    this.player = player;
    this.actionType = actionType;
    this.actionData = actionData;
  }

  async distributeRewards() {
    const baseReward = this.calculateBaseReward();
    const bonusReward = await this.calculateBonusReward();
    const totalReward = baseReward + bonusReward;

    await this.mintRewardTokens(totalReward);
    this.updatePlayerStats(totalReward);

    return totalReward;
  }

  calculateBaseReward() {
    const rewardRates = {
      combat: 10,
      capture: 20,
      trade: 5,
      training: 15
    };
    return rewardRates[this.actionType] || 0;
  }

  async calculateBonusReward() {
    // Complex bonus calculation, potentially using AI to assess performance
    const response = await fetch('https://ai.monster.api/calculate-bonus', {
      method: 'POST',
      body: JSON.stringify({
        actionType: this.actionType,
        actionData: this.actionData,
        playerHistory: this.player.recentActions
      }),
      headers: { 'Content-Type': 'application/json' }
    });
    const { bonusReward } = await response.json();
    return bonusReward;
  }

  async mintRewardTokens(amount) {
    // Interact with blockchain to mint and transfer tokens
    const transaction = await tokenContract.methods.mintAndTransfer(
      this.player.walletAddress,
      amount
    ).send({ from: gameWalletAddress });
    console.log(`Minted ${amount} tokens to ${this.player.walletAddress}`);
    return transaction;
  }

  updatePlayerStats(rewardAmount) {
    this.player.totalEarnings += rewardAmount;
    this.player.recentActions.push({
      type: this.actionType,
      reward: rewardAmount,
      timestamp: Date.now()
    });
  }
}

// Usage
const rewardSystem = new P2ERewardSystem(currentPlayer, 'combat', combatResult);
const rewardAmount = await rewardSystem.distributeRewards();
console.log(`Player earned ${rewardAmount} tokens`);

This example demonstrates a P2E reward system that calculates and distributes rewards based on player actions, incorporating both base rates and AI-calculated bonuses.

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Last updated 2 months ago