Multi-Agent Consensus Seeking via Large Language Models

Multi-agent systems driven by large language models (LLMs) have shown promising abilities for solving complex tasks in a collaborative manner. This work considers a fundamental problem in multi-agent collaboration: consensus seeking. When multiple agents work together, we are interested in how they can reach a consensus through inter-agent negotiation. To that end, this work studies a consensus-seeking task where the state of each agent is a numerical value and they negotiate with each other to reach a consensus value. It is revealed that when not explicitly directed on which strategy should be adopted, the LLM-driven agents primarily use the average strategy for consensus seeking although they may occasionally use some other strategies. Moreover, this work analyzes the impact of the agent number, agent personality, and network topology on the negotiation process. The findings reported in this work can potentially lay the foundations for understanding the behaviors of LLM-driven multi-agent systems for solving more complex tasks. Furthermore, LLM-driven consensus seeking is applied to a multi-robot aggregation task. This application demonstrates the potential of LLM-driven agents to achieve zero-shot autonomous planning for multi-robot collaboration tasks. Project website: westlakeintelligentrobotics.github.io/ConsensusLLM/

Optimal Spatial-Temporal Triangulation for Bearing-Only Cooperative Motion Estimation

Vision-based cooperative motion estimation is an important problem for many multi-robot systems such as cooperative aerial target pursuit. This problem can be formulated as bearing-only cooperative motion estimation, where the visual measurement is modeled as a bearing vector pointing from the camera to the target. The conventional approaches for bearing-only cooperative estimation are mainly based on the framework distributed Kalman filtering (DKF). In this paper, we propose a new optimal bearing-only cooperative estimation algorithm, named spatial-temporal triangulation, based on the method of distributed recursive least squares, which provides a more flexible framework for designing distributed estimators than DKF. The design of the algorithm fully incorporates all the available information and the specific triangulation geometric constraint. As a result, the algorithm has superior estimation performance than the state-of-the-art DKF algorithms in terms of both accuracy and convergence speed as verified by numerical simulation. We rigorously prove the exponential convergence of the proposed algorithm. Moreover, to verify the effectiveness of the proposed algorithm under practical challenging conditions, we develop a vision-based cooperative aerial target pursuit system, which is the first of such fully autonomous systems so far to the best of our knowledge

Remote Network Monitoring Technology Based on Computer Technology

AbstractWith the rapid development of Internet technology, using images to express the characteristics of things more direct, compared with text, audio, image expression content is more ambiguous, which makes the rapid increase of digital images on the Internet. Nowadays one of the hot directions of computer vision research is how to accurately and quickly retrieve the target image from a large amount of image data. This paper summarizes the development of image retrieval technology at home and abroad, and proposes an image search method based on color histogram and Chi-square distance. This paper discusses how to construct an image search system, which can search the image quickly, describe the color distribution of the photo with color histogram, divide the image into five regions, extract image features from the color histogram of each region, and then get the data set of multi-dimensional image features. Then the chi-square distance is used to calculate the similarity of color histogram, and the closest image is selected as the first similar image, which realizes the necessary logic of receiving query image and returning related results.</jats:p

Mechanisms of Danggui Buxue Tang on Hematopoiesis via Multiple Targets and Multiple Components: Metabonomics Combined with Database Mining Technology

This study aimed to explore the mechanism of action of Danggui Buxue Tang (DBT) with its multiple components and targets in the synergistic regulation of hematopoiesis. Mouse models of hematopoiesis were established using antibiotics. Metabolomics was used to detect body metabolites and enriched pathways. The active ingredients, targets, and pathways of DBT were analyzed using system pharmacology. The results of metabolomics and system pharmacology were integrated to identify the key pathways and targets. A total of 515 metabolites were identified using metabolomics. After the action of antibiotics, 49 metabolites were markedly changed: 23 were increased, 26 were decreased, and 11 were significantly reversed after DBT administration. Pathway enrichment analysis showed that these 11 metabolites were related to bile secretion, cofactor biosynthesis, and fatty acid biosynthesis. The results of the pharmacological analysis showed that 616 targets were related to DBT-induced anemia, which were mainly enriched in biological processes, such as bile secretion, biosynthesis of cofactors, and cholesterol metabolism. Combined with the results of metabolomics and system pharmacology, we found that bile acid metabolism and biotin synthesis were the key pathways for DBT. Forty-two targets of DBT were related to these two metabolic pathways. PPI analysis revealed that the top 10 targets were CYP3A4, ABCG2, and UGT1A8. Twenty-one components interacted with these 10 targets. In one case, a target corresponds to multiple components, and a component corresponds to multiple targets. DBT acts on multiple targets of ABCG2, UGT1A8, and CYP3A4 through multiple components, affecting the biosynthesis of cofactors and bile secretion pathways to regulate hematopoiesis. </jats:p