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 ...
In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine ...
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 ...
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 ...
As an important mathematical model, the finite state machine (FSM) has been used in many fields, such as manufacturing system, health care, and so on. This paper analyzes the current development ...
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