Multi-Objective Reinforcement Learning (MORL) is an emerging field that extends the conventional reinforcement learning paradigm by enabling agents to optimise multiple conflicting objectives ...
ANN ARBOR (WWJ) --The supply chain design software developer LLamasoft this week introduced what it called multi-objective optimization technology that enables businesses to analyze the trade-offs ...
Lan, M. H. (2025) Multi-Objective Evolutionary Optimization for Qujing’s Cultural-Tourism Routes. Journal of Data Analysis ...
Journal of Urban and Environmental Engineering, Vol. 10, No. 1 (January to June 2016), pp. 42-49 (8 pages) Abstract: Land use planning seeks to divide land, the most valuable resource in the hands of ...
This is a preview. Log in through your library . Abstract This paper discusses the use of a Multi-Objective Genetic Algorithm to optimize a technology portfolio for a commercial transport. When ...
Water markets have developed around the world due to efforts to reallocate water supply and promote efficient and sustainable use of water. Although creators of water markets commonly share a desire ...
Researchers from Standford, Princeton, and Cornell have developed a new benchmark to better evaluate coding abilities of large language models (LLMs). Called CodeClash, the new benchmark pits LLMs ...
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