Artificial intelligence in the creative industries: a review
N Anantrasirichai, D Bull - Artificial intelligence review, 2022 - Springer
This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …
applications in the context of the creative industries. A brief background of AI, and …
Reinforcement Learning in Education: A Literature Review
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 …
to bring about a significant shift in the way students approach and engage with learning and …
Where's the reward? a review of reinforcement learning for instructional sequencing
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 …
activities using the tools of reinforcement learning (RL) and sequential decision making …
DeepStealth: Game-Based Learning Stealth Assessment With Deep Neural Networks
A distinctive feature of game-based learning environments is their capacity for enabling
stealth assessment. Stealth assessment analyzes a stream of fine-grained student …
stealth assessment. Stealth assessment analyzes a stream of fine-grained student …
Data-driven artificial intelligence in education: A comprehensive review
As education constitutes an essential development standard for individuals and societies,
researchers have been exploring the use of artificial intelligence (AI) in this domain and …
researchers have been exploring the use of artificial intelligence (AI) in this domain and …
Get a head start: On-demand pedagogical policy selection in intelligent tutoring
Reinforcement learning (RL) is broadly employed in human-involved systems to enhance
human outcomes. Off-policy evaluation (OPE) has been pivotal for RL in those realms since …
human outcomes. Off-policy evaluation (OPE) has been pivotal for RL in those realms since …
Reinforcement learning for personalization: A systematic literature review
The major application areas of reinforcement learning (RL) have traditionally been game
playing and continuous control. In recent years, however, RL has been increasingly applied …
playing and continuous control. In recent years, however, RL has been increasingly applied …
Short-term forecasting of wind energy: A comparison of deep learning frameworks
E Mora, J Cifuentes, G Marulanda - Energies, 2021 - mdpi.com
Wind energy has been recognized as the most promising and economical renewable
energy source, attracting increasing attention in recent years. However, considering the …
energy source, attracting increasing attention in recent years. However, considering the …
A generalized apprenticeship learning framework for modeling heterogeneous student pedagogical strategies
A key challenge in e-learning environments like Intelligent Tutoring Systems (ITSs) is to
induce effective pedagogical policies efficiently. While Deep Reinforcement Learning (DRL) …
induce effective pedagogical policies efficiently. While Deep Reinforcement Learning (DRL) …
Hierarchical reinforcement learning for pedagogical policy induction
In interactive e-learning environments such as Intelligent Tutoring Systems, there are
pedagogical decisions to make at two main levels of granularity: whole problems and single …
pedagogical decisions to make at two main levels of granularity: whole problems and single …