[Podcast] Efficient Agents: Optimizing Memory, Tool Learning, and Planning скачать в хорошем качестве

[Podcast] Efficient Agents: Optimizing Memory, Tool Learning, and Planning

Efficient Agents: Optimizing Memory, Tool Learning, and Planning https://www.alphaxiv.org/abs/2601.14192 This research paper provides a comprehensive analysis of agent efficiency, moving beyond simple model compression to address the high costs of recursive workflows. The authors explore the lifecycle of efficient memory, detailing how construction, management, and access strategies can mitigate token explosion and latency during long-term interactions. They also examine tool learning, highlighting methods for precise selection and cost-aware invocation to prevent unnecessary external calls. Furthermore, the text categorizes efficient planning techniques, contrasting single-agent adaptive control with multi-agent topological optimization to reduce communication overhead. Finally, the sources review emerging benchmarks that prioritize the Pareto frontier between task effectiveness and resource consumption. This synthesis frames the development of autonomous systems as a budget-constrained control problem rather than just an exercise in expanding reasoning capabilities. #ai #agent #research Disclaimer: This video is generated with Google's NotebookLM.