Architectural Patterns for Self-Improving Intelligent Agents: A Systematic Survey of Generative and Cognitive Approaches

Autonomous AI agents and recursive self-improvement: a comprehensive survey of contemporary architectures, capabilities, and safety frameworks

From Language Models to Agentic AI: A Survey of Autonomous, Action-Enabled, and Collaborative LLM Agents

A unified, taxonomy-driven, and deployment-oriented survey of agentic AI systems, synthesizing recent advances through a modular reference architecture and a four-dimensional taxonomy that characterizes agents along the axes of autonomy, tool use, collaboration, and safety–governance is presented.

LLM-Based Autonomous Agents: A Systematic Review and Critical Synthesis of Architectural Paradigms, Memory Models, Planning Strategies, And Operational Limitations

A consolidated analytical framework is proposed that maps common structural elements and trade-offs across reviewed systems, and outlines a research agenda directed toward formalised agent architectures, memory consistency guarantees, verified planning algorithms, standardised reliability metrics, and benchmark framewo...

Large Language Models for Self-Adaptive Systems: Feedback-Loop Integration and Agentic Adaptation

Learning from Research: Toward Lifelong Agent Harness Evolution

Language agents are expected to solve increasingly complex tasks, creating a growing need for continual improvement. One promising approach is to evolve the agent harness, the software that governs tool use, memory management, and task execution, while keeping the underlying language model fixed. Recent methods automat...

Bringing AI to Autonomous Systems -- From Cognition to Collective Intelligence

A comprehensive framework for the design and evaluation of autonomous systems, based on a generic agent architecture that characterizes their behavior as the composition of cognitive functions organized around a long-term memory containing the agent's evolving knowledge.