Artificially Intelligent (AI) Agent
(Redirected from Intelligent software agent)
Jump to navigation
Jump to search
An Artificially Intelligent (AI) Agent is a software-based agent that is an autonomous AI system (which implements AI agent algorithms to perform AI agent tasks through environmental interaction and autonomous decision making).
- Context:
- It can (typically) process Agent Input through AI models and learning algorithms.
- It can (typically) generate Agent Actions via automated decision making.
- It can (typically) interact with its Agent Environment through sensor and actuator systems.
- It can (often) adapt its Agent Behavior through continuous learning.
- It can (often) collaborate with other AI Agents in multi-agent systems.
- It can (often) initiate Agent Tasks based on environmental triggers.
- ...
- It can range from being a Simple AI Agent to being a Complex AI Agent, depending on its agent functionality complexity.
- It can range from being a Specific AI Agent to being a General AI Agent, depending on its agent domain adaptability.
- It can range from being a Rule-based AI Agent to being a Learning-based AI Agent, depending on its agent learning capability.
- It can range from being a Supervised AI Agent to being an Unsupervised AI Agent, depending on its agent training requirement.
- It can range from being a Single-agent AI System to being a Multi-agent AI System, depending on its agent collaboration capability.
- It can range from being a Local AI System to being a Global AI System, depending on its agent operational scope.
- It can range from being a Physical AI System to being a Virtual AI System, depending on its agent embodiment type.
- It can range from being a Passive AI System to being an Active AI System, depending on its agent initiation capability.
- It can range from being a Human-like AI System to being a Non-human-like AI System, depending on its agent behavioral similarity.
- It can range from being a Narrow AI Agent to being a General AI Agent, depending on its capability scope.
- It can range from being an Athletic AI Agent to being a Scholarly AI Agent, depending on its task domain.
- It can range from being a Domain-Specific AI Agent to being an Open-Domain AI Agent, depending on its application scope.
- It can range from being a Non-Cognitive AI Agent to being a Cognitive AI Agent, depending on its reasoning capability.
- It can range from being an Engineered AI Agent to being an Evolved AI Agent, depending on its development approach.
- It can range from being an Information Providing AI Agent to being a Tool Using AI Agent, depending on its interaction mode.
- It can range from being a Black-Box AI Agent to being an Explainable AI Agent, depending on its transparency level.
- It can range from being a Beneficial AI Agent to being a Dangerous AI Agent, depending on its impact type.
- It can range from being a Rule-Based AI Agent to being a Language Model AI Agent, depending on its system complexity.
- ...
- Examples:
- Reactive AI Agents, which respond to specific stimuli.
- Proactive AI Agents, such as:
- ChatGPT-based Agent (2024), generating follow-up questions after strategy setup.
- Planning Agent, anticipating future states and action sequences.
- Task-Oriented AI Agents, such as:
- Simple AI Agent, performing basic functions.
- Complex AI Agent, managing advanced features.
- Specific AI Agent, focusing on specialized tasks.
- General AI Agent, handling diverse task types.
- Learning-Based AI Agents, such as:
- Rule-based AI Agent, following predefined rules.
- Learning-based AI Agent, adapting through experience.
- Supervised AI Agent, trained on labeled data.
- Unsupervised AI Agent, learning from unlabeled data.
- System Architecture AI Agents, such as:
- Single-agent AI System, operating independently.
- Multi-agent AI System, enabling agent collaboration.
- Local AI System, functioning in confined environments.
- Global AI System, operating across distributed networks.
- Implementation AI Agents, such as:
- Physical AI System, like Roomba Robot (2024), performing physical tasks.
- Virtual AI System, like ChatGPT-based Agent (2024), operating as a web-based application.
- Behavioral AI Agents, such as:
- Passive AI System, maintaining static behavior.
- Active AI System, showing adaptive responses.
- Human-like AI System, mimicking human behavior.
- Non-human-like AI System, using alternative behavior patterns.
- Intelligent Software Assistant.
- ...
- Counter-Examples:
- Unintelligent Software Agents, which lack AI capabilitys.
- Manual Control Systems, requiring constant human input.
- Static Algorithms, without learning ability.
- Pure Data Storages, lacking agent behavior.
- See: ChatGPT-based Agent, Chatbot-based Agent, Autonomous AI System, Agent Learning, AI Architecture, Multi-Agent System.
References
2023
- chat
- AI Agent Properties Table:
Examples | Reactive AI Agent | Proactive AI Agent | Simple AI Agent | Complex AI Agent | Specific AI Agent | General AI Agent | Rule-based AI Agent | Learning-based AI Agent | Supervised AI Agent | Unsupervised AI Agent | Single-agent AI System | Multi-agent AI System | Local AI System | Global AI System | Physical AI System | Virtual AI System | Passive AI System | Active AI System | Human-like AI System | Non-human-like AI System | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Light-sensitive robots moving towards/away from light sources | X | X | X | X | X | X | |||||||||||||||
Personal assistants predicting user's next action | X | X | X | X | X | ||||||||||||||||
Basic chatbots answering predefined queries | X | X | X | X | X | ||||||||||||||||
Image recognition systems diagnosing specific diseases | X | X | X | ||||||||||||||||||
General purpose robotics systems adaptable to tasks | X | X | X | X | |||||||||||||||||
Legacy expert systems in medical diagnosis | X | X | X | ||||||||||||||||||
Autonomous cars learning from on-road experiences | X | X | X | X | X | ||||||||||||||||
Recommendation systems refining suggestions based on behavior | X | X | X | X | |||||||||||||||||
Image classifiers trained on labeled datasets | X | X | |||||||||||||||||||
Anomaly detection systems in network security | X | X | |||||||||||||||||||
Standalone virtual customer service agents on websites | X | X | |||||||||||||||||||
Swarm robotics used for coordinated tasks like search and rescue | X | X | X | X | X | X | |||||||||||||||
Home automation systems controlling devices in a house | X | X | X | ||||||||||||||||||
Global weather prediction systems | X | X | X | X | X | X | |||||||||||||||
Warehouse robots for sorting and moving items | X | X | X | X | |||||||||||||||||
Virtual assistants on smartphones or computers | X | X | X | X | |||||||||||||||||
Humanoid robots for social interaction or companionship | X | X | X | X | |||||||||||||||||
Industrial robotic arms for manufacturing | X | X | X |