33 stories tagged Decision Making · page 2 of 2
Researchers have developed a better way for AI to handle complex reasoning by tracking its thought process and knowing when to stop. This could make AI assistants and decision-making tools more reliable for everyday use.
Researchers have developed a new AI framework called PRISM that helps AI agents make better decisions by tightly connecting what they see with how they think. This could improve AI assistants that interact with the real world, like robots or smart home systems.
Researchers found that large language models (LLMs) have trouble making strategic decisions because they can't properly connect what they observe with what they believe. This affects AI in negotiations and policymaking. The study tested models like Llama 3.1 and Qwen3.
A new study explores how Large Language Models (LLMs) respond to legal arguments and the factors influencing their decisions. The research highlights the importance of understanding LLMs' persuadability in judicial and administrative contexts.
Researchers developed a novel approach for LLMs to co-evolve decision-making and skill banks, significantly improving performance in complex, long-horizon game environments. This method addresses key challenges in multi-step reasoning and delayed rewards.
Researchers propose a method for AI agents to predict future events by tracking evolving public evidence. This could improve decision-making in uncertain scenarios where outcomes are initially unknown.
A comprehensive survey reviews the use of Explainable AI (XAI) to make surrogate models more interpretable. The study highlights the need for transparency in complex simulations across scientific and engineering fields. This work offers a roadmap for integrating XAI into decision-making processes.
Researchers have developed a method to quantify exploration and exploitation in language model agents without accessing their internal policies. This breakthrough could improve AI decision-making in complex tasks.
A new study explores how emotions affect decision-making in small language models (SLMs) by using activation steering for controlled emotional states. The research introduces a game-theoretic benchmark to evaluate these interactions.