Zobrazeno 1 - 10
of 1 890
pro vyhledávání: '"i.2.8"'
Autor:
Yousaf, Iqra
This research investigates the use of artificial intelligence and machine learning techniques to predict the toxicity of nanoparticles, a pressing concern due to their pervasive use in various industries and the inherent challenges in assessing their
Externí odkaz:
http://arxiv.org/abs/2409.15322
Autor:
Zampella, Maria, Otamendi, Urtzi, Belaunzaran, Xabier, Artetxe, Arkaitz, Olaizola, Igor G., Longo, Giuseppe, Sierra, Basilio
Scheduling problems pose significant challenges in resource, industry, and operational management. This paper addresses the Unrelated Parallel Machine Scheduling Problem (UPMS) with setup times and resources using a Multi-Agent Reinforcement Learning
Externí odkaz:
http://arxiv.org/abs/2411.07634
Autor:
Asgharian-Sardroud, Asghar, Izanlou, Mohammad Hossein, Jabbari, Amin, Hamedani, Sepehr Mahmoodian
Network function virtualization enables network operators to implement new services through a process called service function chain mapping. The concept of Service Function Chain (SFC) is introduced to provide complex services, which is an ordered se
Externí odkaz:
http://arxiv.org/abs/2411.07606
Autor:
Sidorov, Konstantin, van der Linden, Koos, Correia, Gonçalo Homem de Almeida, de Weerdt, Mathijs, Demirović, Emir
Modern software for propositional satisfiability problems gives a powerful automated reasoning toolkit, capable of outputting not only a satisfiable/unsatisfiable signal but also a justification of unsatisfiability in the form of resolution proof (or
Externí odkaz:
http://arxiv.org/abs/2411.07955
Large Language Models (LLMs) excel in diverse applications including generation of code snippets, but often struggle with generating code for complex Machine Learning (ML) tasks. Although existing LLM single-agent based systems give varying performan
Externí odkaz:
http://arxiv.org/abs/2411.07464
Autor:
Liang, Yuanchu, Kim, Edward, Thomason, Wil, Kingston, Zachary, Kurniawati, Hanna, Kavraki, Lydia E.
Partially Observable Markov Decision Processes (POMDPs) are a general and principled framework for motion planning under uncertainty. Despite tremendous improvement in the scalability of POMDP solvers, long-horizon POMDPs (e.g., $\geq15$ steps) remai
Externí odkaz:
http://arxiv.org/abs/2411.07032
Term rewriting plays a crucial role in software verification and compiler optimization. With dozens of highly parameterizable techniques developed to prove various system properties, automatic term rewriting tools work in an extensive parameter space
Externí odkaz:
http://arxiv.org/abs/2411.06409
A popular method for Neural Architecture Search (NAS) is based on growing networks via small local changes to the network's architecture called network morphisms. These methods start with a small seed network and progressively grow the network by add
Externí odkaz:
http://arxiv.org/abs/2411.05855
This paper presents the Random-Key Optimizer (RKO), a versatile and efficient stochastic local search method tailored for combinatorial optimization problems. Using the random-key concept, RKO encodes solutions as vectors of random keys that are subs
Externí odkaz:
http://arxiv.org/abs/2411.04293
The application of intelligent decision-making in unmanned aerial vehicle (UAV) is increasing, and with the development of UAV 1v1 pursuit-evasion game, multi-UAV cooperative game has emerged as a new challenge. This paper proposes a deep reinforceme
Externí odkaz:
http://arxiv.org/abs/2411.02983