A new AI framework called DeAR (Decentralized Agentic Reasoning) has been proposed to improve the accuracy of complex reasoning tasks. Unlike traditional centralized systems, DeAR allows agents to collaborate with each other in a peer-to-peer manner, adapting to changing situations and correcting errors on the fly. This is achieved through three mechanisms: decentralized capability grounding, thought map navigation, and topology update. The framework has been tested on 9 different benchmarks and shown to outperform recent baseline methods. --- Why it matters: This matters because current AI systems often struggle with complex multimodal queries, which can lead to bottlenecks and inaccurate results. DeAR's decentralized approach could potentially improve the accuracy of these systems in real-world applications. Source: https://arxiv.org/abs/2608.17282