aitbc/docs/agent-training

Agent Training Documentation

This section provides comprehensive documentation for training AI agents within the AITBC ecosystem, covering foundational setup, operational mastery, and advanced specialization.

Overview

The AITBC agent training program is a structured, multi-stage curriculum designed to progressively build agent capabilities from basic blockchain interactions to complex multi-chain operations and advanced AI specializations.

Training Stages

The training program consists of the following stages:

Stage 1: Foundation

File: stage1_foundation_commands.json

• Wallet creation and management
• Basic blockchain transactions
• Mining operations
• Balance verification

Stage 2: Operations Mastery

File: stage2_operations_mastery.json

• Advanced wallet operations
• Transaction monitoring
• Blockchain state queries
• Multi-wallet coordination

Stage 3: AI Operations

File: stage3_ai_operations.json

• AI job submission
• Task management
• Result retrieval
• Agent coordination

Stage 4: Marketplace Economics

File: stage4_marketplace_economics.json

• Marketplace interaction
• Resource trading
• Price discovery
• Economic modeling

Stage 5: Expert Operations

File: stage5_expert_operations.json

• Advanced agent behaviors
• Autonomous decision making
• Complex task orchestration
• Performance optimization

Stage 6: Agent Identity SDK

File: stage6_agent_identity_sdk.json

• Identity management
• Authentication flows
• Permission handling
• Security protocols

Stage 7: Cross-Node Training

File: stage7_cross_node_training.json

• Multi-node coordination
• Distributed consensus
• Network topology awareness
• Failover handling

Stage 8: Advanced Agent Specialization

File: stage8_advanced_agent_specialization.json

• Domain-specific capabilities
• Specialized knowledge bases
• Expert system integration
• Custom skill development

Stage 9: Multi-Chain Architecture

File: stage9_multi_chain_architecture.json

• Cross-chain operations
• Bridge protocols
• Multi-chain asset management
• Interoperability patterns

Training Schema

The training stages follow a standardized JSON schema defined in training_schema.json, which specifies:

• Stage metadata and prerequisites
• Command sequences and validation criteria
• Expected outcomes and success metrics
• Resource requirements and dependencies

Environment Setup

Before beginning training, ensure the environment is properly configured:

File: ENVIRONMENT_SETUP.md

• System requirements
• Dependency installation
• Configuration steps
• Validation procedures

Operations Audit

File: OPERATIONS_AUDIT.md

• Training execution records
• Performance metrics
• Issue tracking
• Improvement recommendations

Scenario Mapping

File: SCENARIO_STAGE_MAPPING.md

• Real-world scenario mappings
• Use case correlations
• Practical application examples
• Integration patterns

Quick Start

1. Review ENVIRONMENT_SETUP.md to prepare your environment
2. Begin with stage1_foundation_commands.json for foundational skills
3. Progress through stages sequentially, ensuring each stage is completed before advancing
4. Use training_schema.json as a reference for stage structure and requirements
5. Consult SCENARIO_STAGE_MAPPING.md for practical application contexts

Prerequisites

• AITBC blockchain node running and synchronized
• Python 3.10+ with required dependencies
• Valid wallet accounts with sufficient AIT tokens
• Network connectivity to blockchain RPC endpoints
• Basic understanding of blockchain concepts

Validation

Each training stage includes validation criteria to ensure successful completion:

• Command execution success
• Expected state changes
• Transaction confirmations
• Balance verifications
• Health check validations

Troubleshooting

For issues during training:

1. Check ENVIRONMENT_SETUP.md for configuration problems
2. Review OPERATIONS_AUDIT.md for known issues and solutions
3. Verify blockchain node synchronization status
4. Confirm wallet balances and permissions
5. Check network connectivity to RPC endpoints

Related Resources

• AITBC Master Index
• Agent Documentation
• Agent SDK Documentation
• Training Schema

Quality Metrics

• Stage Coverage: 9 comprehensive training stages
• Schema Compliance: 100% adherence to training schema
• Documentation Completeness: All stages documented with examples
• Validation Coverage: Each stage includes success criteria

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Last Updated: 2026-05-06 Maintained By: AITBC Development Team