Leveraging LLMs to Integrate Expert Knowledge into Algorithmic Planning,” presented at the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026), introduces a hybrid ...
Gaussian processes (GPs) have attracted considerable attention in assisting evolutionary algorithms (EAs) to solve computationally expensive optimization problems (EOPs) because they can directly ...
In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...
Want your business to show up in Google’s AI-driven results? The same principles that help you rank in Google Search still matter – but AI introduces new dimensions of context, reputation, and ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In the past, sulfur present in fossil fuels would usually end ...
Abstract: With autonomous robots becoming increasingly integrated into human society, the efficiency of their path optimization is of paramount importance. To address the issue of redundant states in ...
A reward shaping deep deterministic policy gradient (RS-DDPG) and simultaneous localization and mapping (SLAM) path tracking algorithm is proposed to address the issues of low accuracy and poor ...
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