It always amazed me that different branches of CS, AI/ML and Complex Systems/Complexity Sciences have different views on agents. Objects in OOP - something whi

It always amazed me that different branches of CS, AI/ML and Complex Systems/Complexity Sciences have different views on agents. Objects in OOP - something which can have properties/attributes, and methods (verbs/commands). Usually modeled after a real-life/domain enitites. Aggregates in Domain-Driven Design (DDD) - transactional clusters of objects modeling a collections of entities in the domain. Actors in Actor Model / Active Objects - a something we can sen messages to, and receive messages from, and which may have some business logic. Agent-Based Modeling and Simulations (ABM) defines agents as a proxy for a decision maker. Digital Twins - a more realistic proxy/replica for a real life person, object, or process. Multi-Agent Systems (MAS) in how to use asgents to solve or optimize a real problem in production. RL/MARL (Muti-Agent Reinforcement Learning) on how to train an ML algorithm without supervision (i.e. a labeled dataset), by placing agents in an environment capable to automatically provide rewards/punishment feedback. LLM Agents - dynamically generated intelligent business process workflows (including Robotic Process Automation - RPA aka Tool Use/Function Call).