Princeton University researchers have introduced a new framework, “Cognitive Architectures for Language Agents (CoALA).” This is designed to better integrate large language models (LLMs) with external resources and enhance their control flows. While LLMs have revolutionized NLP, they still face challenges in understanding real-world knowledge and interacting externally. To address this, enhancements have led to the development of “language agents,” which use LLMs in sequential decision-making. The CoALA framework draws inspiration from historical “production systems” and “cognitive architectures,” suggesting LLMs can benefit from their approaches. Through this, Princeton's team highlights the potential for future AI agents that are more context-aware and grounded.
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Princeton University Researchers Unveils CoALA, an Advanced Framework for Cognitive Language Agents
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