Human Thinking

Research on human thinking aims to understand and replicate the complex cognitive processes underlying reasoning, problem-solving, and decision-making. Current efforts focus on developing large language models (LLMs) that can perform various reasoning types (deductive, inductive, abductive, analogical) and incorporate "thinking" steps into their processes, often using novel architectures like Graph of Thoughts or dual cognition-action models. These advancements are significant because they offer insights into human cognition and have the potential to improve AI systems' ability to solve complex problems and assist in decision-making across various fields. Furthermore, research is exploring how to evaluate and improve the critical thinking capabilities of LLMs, moving beyond simple accuracy metrics to assess the quality and robustness of their reasoning.