Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

The utilization of reinforcement learning (RL) within the field of education holds the potential
to bring about a significant shift in the way students approach and engage with learning and …

Reinforcement learning (RL) is a popular paradigm for addressing sequential decision tasks
in which the agent has only limited environmental feedback. Despite many advances over …

Risks of work-related musculoskeletal injuries can be reduced by adequately training
construction workers on performing work in safe postures. Traditional training approaches …

Effective and engaging E-learning becomes necessary in unusual conditions such as
COVID-19 pandemic, especially for the early stages of K-12 education. This paper proposes …

Since the 1960s, researchers have been trying to optimize the sequencing of instructional
activities using the tools of reinforcement learning (RL) and sequential decision making …

For many forms of e-learning environments, the system's behavior can be viewed as a
sequential decision process wherein, at each discrete step, the system is responsible for …

The development of mechanisms to understand and model the expected behaviour of
multiagent learners is becoming increasingly important as the area rapidly find application in …

Abstract The use of Artificial Intelligence (AI) and Machine Learning algorithms is surging in
education. One of these methods, called Reinforcement Learning (RL) may be considered …

Wireless sensor networks (WSNs) have been widely investigated in recent years. One of the
fundamental issues in WSNs is packet routing, because in many application domains …