Autonomous Intelligent Machine

An Autonomous Intelligent Machine is an intelligent agent that is an AI system.

• AKA: Non-Human Intelligence, Intelligent Agent System.
• Context:
  • It can (typically) be based on AI Technologies, such as: machine learning, deep learning, [[natural language [rocessing]], and computer vision.
  • It can (often) exhibit System Behaviors, such as: adaptive learning, decision making, problem solving, and autonomous navigation.
  • It can range from being a Conscious Intelligent Machine to being an Non-Conscious Intelligent Machine.
  • It can range from (typically) being a Linguistic AI Machine to being a Visual AI Machine.
  • It can operate in a variety of domains, from (often) Autonomous Vehicles and Medical Diagnosis Systems to Automated Financial Trading Systems and Smart Home Technologies.
  • ...
• Example(s)
  • HAL 9000.
  • one based on Auto-GPT.
  • an LLM-based Agent, such as Vogager AI agent.
  • a Self-Driving Car utilizing complex AI algorithms for navigation and safety.
  • a Predictive Maintenance Robot in industrial settings, foreseeing machinery failures before they occur.
  • …
• Counter-Example(s):
  • a Non-Intelligent Mechanical Agent, such as a Roomba robot or an ASIMO robot.
  • an Intelligent Virtual Assistant, due to its limited autonomy and dependence on human-defined rules.
  • an Intelligent Living Agent, an intelligent person.
  • a Heuristic-based Autonomous System, as it operates based on set rules rather than learning from data.
  • a Corporation, because it is not a machine.
• See: Intelligent System, Moral Machine, AI Emotion, Advanced AI System, Machine Ethics, Human-AI Collaboration, Artificial General Intelligence.

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References

2017

• (Institute, 2017) ⇒ The Future of Life Institute. (2017). “Asilomar AI Principles.”
  • QUOTE: ...
    • 8) Judicial Transparency: Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority.
    • …
    • 10) Value Alignment: Highly autonomous AI systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation.

2006

• Stan Franklin, and F. G. Patterson Jr. (2006). “The LIDA architecture: Adding new modes of learning to an intelligent, autonomous, software agent.” In: Integrated Design and Process Technology, IDPT-2006

2001

• (Addlesee et al., 2001) ⇒ Mike Addlesee, Rupert Curwen, Steve Hodges, Joe Newman, Pete Steggles, Andy Ward, and Andy Hopper. (2001). “Implementing a Sentient Computing System.” In: Computer Journal, 34(8). doi:10.1109/2.940013
  • QUOTE: Sentient computing systems, which can change their behavior based on a model of the environment they construct using sensor data,

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