Sichkar V. N. "Reinforcement Learning Algorithms in Global Path Planning for Mobile Robot", 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), Sochi, ...
We consider the problem of fitting a reinforcement learning (RL) model to some given behavioral data under a multi-armed bandit environment. These models have received much attention in recent years ...
To provide quantitative analysis of strategic confrontation game such as cross-border trades like tariff disputes and competitive scenarios like auction bidding, we propose an alternating Markov ...
A high-fidelity Python implementation of the Q-learning oligopoly simulation from Calvano et al. (2020). This project provides a complete, tested, and extensible reproduction of the seminal study ...
The intensification of urbanisation and climate change poses significant challenges to global food security, prompting the exploration of innovative agricultural solutions such as urban vertical ...
In today’s world, sustainable development is a major priority, and the combination of renewable energy sources with microgrids has revolutionized energy distribution systems. Microgrids, with their ...
As machine learning ML and artificial intelligence (AI) continue to transform industries and shape the future of technology gaining a solid understanding of these fields has become more important than ...
Abstract: Distributed Denial of Service (DDoS) threats in Smart Grid are very challenging and considered one of the most destructive cyber-attacks. They are harmfully affecting the power sector and ...
Abstract: This paper presents the hierarchical Q-learning path planning (HQPP) architecture for solving the cooperative tracking control problem of multi-agent systems (MASs) with lumped uncertainties ...
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