Autonomous agent
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An autonomous agent is an artificial intelligence (AI) system that can perform complex tasks independently.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>
Definitions
There are various definitions of autonomous agent. According to Brustoloni (1991):
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According to Maes (1995):
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Franklin and Graesser (1997) review different definitions and propose their definition:
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They explain that:
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Agent appearance
Lee et al. (2015) post safety issue from how the combination of external appearance and internal autonomous agent have impact on human reaction about autonomous vehicles. Their study explores the human-like appearance agent and high level of autonomy are strongly correlated with social presence, intelligence, safety and trustworthiness. In specific, appearance impacts most on affective trust while autonomy impacts most on both affective and cognitive domain of trust where cognitive trust is characterized by knowledge-based factors and affective trust is largely emotion driven.<ref>Template:Cite journal</ref>
Applications
- Agentic AI systems: Advanced AI agents that can scope out projects and complete them with necessary tools, representing a significant evolution from simple task-oriented systems.<ref>{{#invoke:citation/CS1|citation
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- Internet of things (IoT) Integration: Autonomous agents increasingly interact with IoT devices, enabling smart home systems, industrial monitoring, and urban infrastructure management.<ref>{{#invoke:citation/CS1|citation
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- Collaborative software development: Tools like Cognition AI's Devin aim to create autonomous software engineers capable of complex reasoning, planning, and completing engineering tasks requiring thousands of decisions.<ref>{{#invoke:citation/CS1|citation
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Challenges and considerations
- Uncertainty and incomplete information: Autonomous agents must make decisions with limited or uncertain information about their environment and future states.<ref>Template:Cite journal</ref>
- Integration complexity: Incorporating autonomous agents into existing systems and workflows can be technically challenging and resource-intensive.<ref>{{#invoke:citation/CS1|citation
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- Scalability: As systems become more complex and more agents are used, maintaining coordination and avoiding conflicts becomes increasingly difficult.<ref>{{#invoke:citation/CS1|citation
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See also
- Actor model
- Ambient intelligence
- AutoGPT
- Autonomous agency theory
- Chatbot
- Embodied agent
- Intelligent agent
- Intelligent control
- Multi-agent system
- Software agent
References
External links
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