Glossary

Controller: Any algorithm that makes decisions based on programming rather than DRL

Decisions: The outputs of an agent - its instructions for controlling the system

Design patterns: Common structures that can be used to create agents quickly

Episode: An entire performance of the task to success or a set stop condition

Functional Pattern: A Machine Teaching design pattern used to orchestrate skills in sequences

Iteration: One decision during agent training or performance

Learned skills: Skills that use DRL to make decisions and learn by practicing in simulation

Orchestration: Arranging modular building blocks of agents to work together to complete tasks

Perceptor: An ML model or other algorithm that interprets sensor data

Plan-Execute Pattern: A Machine Teaching design pattern used to orchestrate skills in pairs that work together to make decisions

Programmed skills: Skills that make decisions based on programmed algorithms

Project: A collection of agents for the same use case that share the same simulator and top-level goal

Scenarios: Conditions that are associated with specific skills

Selector: A special skill that assigns decision-making control to the right skill based on current conditions

Sensors: Part of the agent that takes in information from the simulator or real system

Simulator: Virtual environment where an agent can practice and improve performance

Skills: Modules within an agent that make decisions to complete all or part of a task

Strategy Pattern: A Machine Teaching design pattern used to orchestrate skills in hierarchies

Teacher: An algorithm that creates a skill that uses DRL to learn to make decisions