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.
- Enterprise automation: Business process automation platforms like Salesforce's Agentforce provide autonomous bots for various service functions.
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.
- Trust: Research has shown the combination of external appearance and internal autonomous capabilities significantly impacts human reactions and trust. Lee et al. (2015) found that human-like appearance and high levels of autonomy are strongly correlated with social presence, intelligence, safety, and trustworthiness perceptions. Specifically, appearance impacts affective trust most significantly, while autonomy affects both affective and cognitive trust domains, where affective trust is emotionally driven, and cognitive trust is characterized by knowledge-based factors.
Ethical and regulatory concerns
- Accountability: Determining responsibility when autonomous agents make incorrect or harmful decisions remains a complex issue.
- Privacy and security: autonomous agents often require access to sensitive data, raising concerns about data protection and system security.
See also
References