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Autonomous agent
Type of autonomous entity in software
Type of autonomous entity in software
An autonomous agent is an artificial intelligence (AI) system that can perform complex tasks independently.
Definitions
There are various definitions of autonomous agent. According to Brustoloni (1991):
According to Maes (1995):
Franklin and Graesser (1997) review different definitions and propose their definition:
They explain that:
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.
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.
- Internet of things (IoT) Integration: Autonomous agents increasingly interact with IoT devices, enabling smart home systems, industrial monitoring, and urban infrastructure management.
- 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.
Challenges and considerations
- Uncertainty and incomplete information: Autonomous agents must make decisions with limited or uncertain information about their environment and future states.
- Integration complexity: Incorporating autonomous agents into existing systems and workflows can be technically challenging and resource-intensive.
- Scalability: As systems become more complex and more agents are used, maintaining coordination and avoiding conflicts becomes increasingly difficult.
References
References
- (April 11, 2024). "Autonomous Agent".
- Lee, Jae-Gil. (Summer 2015). "Can Autonomous Vehicles Be Safe and Trustworthy? Effects of Appearance and Autonomy of Unmanned Driving Systems". International Journal of Human-Computer Interaction.
- (2025-03-04). "AI Agents in 2025: Expectations vs. Reality".
- Onome. (2024-08-21). "State of AI Agents in 2024".
- (2024-11-09). "Autonomous generative AI agents: Under development".
- Scholes, Myron S.. (2025-01-01). "Artificial intelligence and uncertainty". Risk Sciences.
- bambulge, Pratiksha. (2025-09-15). "How AI Agents Are Revolutionizing Software Development Workflows".
- Dungay, David. (2025-01-27). "Bridging the AI Adoption Gap: Employee Resistance and High Costs Remain a Challenge".
- (2025-06-09). "AI agents: Exploring the potential and the problems".
- (1997). "Intelligent Agents III Agent Theories, Architectures, and Languages". Springer Berlin Heidelberg.
- Brustoloni, Jose C.. (1991). "Autonomous Agents: Characterization and Requirements, Carnegie Mellon Technical Report CMU-CS-91-204". Carnegie Mellon University.
- Maes, Pattie. (1995). "Artificial life meets entertainment". Association for Computing Machinery (ACM).
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