Source link : https://tech365.info/alibabas-agentevolver-lifts-mannequin-efficiency-in-instrument-use-by-30-utilizing-artificial-auto-generated-duties/
Researchers at Alibaba’s Tongyi Lab have developed a brand new framework for self-evolving brokers that create their very own coaching information by exploring their software environments. The framework, AgentEvolver, makes use of the information and reasoning capabilities of enormous language fashions for autonomous studying, addressing the excessive prices and handbook effort usually required to assemble task-specific datasets.
Experiments present that in comparison with conventional reinforcement studying–based mostly frameworks, AgentEvolver is extra environment friendly at exploring its atmosphere, makes higher use of knowledge, and adapts sooner to software environments. For the enterprise, that is vital as a result of it lowers the barrier to coaching brokers for bespoke purposes, making highly effective, customized AI assistants extra accessible to a wider vary of organizations.
The excessive price of coaching AI brokers
Reinforcement studying has develop into a significant paradigm for coaching LLMs to behave as brokers that may work together with digital environments and be taught from suggestions. Nevertheless, creating brokers with RL faces elementary challenges. First, gathering the required coaching datasets is usually prohibitively costly, requiring vital handbook labor to create examples of duties, particularly in novel or proprietary software program environments the place there are not any accessible off-the-shelf datasets.
Second, the RL strategies…
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Author : tech365
Publish date : 2025-11-27 20:24:00
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