api_reference.md

EmbodyHub API Reference

Core Components

Agent

Overview

Agent implements high-level intelligent agent logic, including decision making, learning, and adaptation capabilities.

Methods

__init__(adapter, data_manager=None, optimizer=None, config=None)

• Description: Initialize the agent
• Parameters:
  • adapter: Framework adapter instance
  • data_manager: Data manager instance (optional)
  • optimizer: Optimizer instance (optional)
  • config: Configuration dictionary (optional)

act(observation)

• Description: Execute actions based on observations
• Parameters:
  • observation: Environment observation data
• Returns: Selected action

train(env, episodes, optimize=False, eval_interval=100)

• Description: Train the agent
• Parameters:
  • env: Training environment instance
  • episodes: Number of training episodes
  • optimize: Enable optimization (default False)
  • eval_interval: Evaluation interval (default 100)

Environment

Overview

Provides standardized environment interface for agent-environment interactions.

Methods

step(action)

• Description: Execute action and update environment state
• Parameters:
  • action: Action to execute
• Returns: (observation, reward, done, info)

DataManager

Overview

Handles multimodal data streams, supporting data collection, processing, and persistence.

Methods

collect_data(source, data_type)

• Description: Collect data of specified type
• Parameters:
  • source: Data source
  • data_type: Data type
• Returns: Processed data

Advanced Features

Multi-Agent Coordination

Overview

Provides coordination and management capabilities for multi-agent systems.

Key Features

• Inter-agent Communication
• Task Allocation
• Conflict Resolution

Methods

create_agent_group(agents, communication_protocol)

• Description: Create agent group
• Parameters:
  • agents: List of agents
  • communication_protocol: Communication protocol

Performance Optimization

Overview

Provides system performance optimization and auto-tuning capabilities.

Methods

optimize_parameters(model, metrics)

• Description: Optimize model parameters
• Parameters:
  • model: Model to optimize
  • metrics: Optimization metrics

Error Handling

Common Errors

ConfigurationError

• Description: Configuration-related errors
• Solution: Check configuration file format and required parameters

AdapterError

• Description: Adapter-related errors
• Solution: Ensure adapter is properly initialized and configured

Best Practices

Performance Optimization

• Use batch processing for data handling
• Enable performance monitoring
• Set appropriate cache sizes

Memory Management

• Release unused resources promptly
• Use data streams instead of loading all data
• Clear cache periodically