Adaptive patch foraging in deep reinforcement learning agents
Patch foraging is one of the most heavily studied behavioral optimization challenges in
biology. However, despite its importance to biological intelligence, this behavioral …
biology. However, despite its importance to biological intelligence, this behavioral …
The paradox of choice: Using attention in hierarchical reinforcement learning
Decision-making AI agents are often faced with two important challenges: the depth of the
planning horizon, and the branching factor due to having many choices. Hierarchical …
planning horizon, and the branching factor due to having many choices. Hierarchical …
Design of music teaching system based on artificial intelligence
W Chen - Mathematical Problems in Engineering, 2022 - Wiley Online Library
This paper analyzes the application basis of AI technology in music teaching and realizes
the extraction of music features. In addition, an intelligent music teaching model based on …
the extraction of music features. In addition, an intelligent music teaching model based on …
[PDF][PDF] The BioShield Algorithm: Pioneering Real-Time Adaptive Security in IoT Networks through Nature-Inspired Machine Learning
C Rammohan, P Laxmikanth, D Srikar… - … Journal of Security …, 2023 - researchgate.net
This paper introduces the BioShield Algorithm, aimed at the crucial task of securing IoT
networks through real-time adaptive mechanisms that draw inspiration from nature. It delves …
networks through real-time adaptive mechanisms that draw inspiration from nature. It delves …
Emergent prosocial behavior during dynamic human group formation
For scientists, policy makers, and the general population, there is increasing interest in how
humans form cooperative groups. Probing the changes that emerge in cognition as group …
humans form cooperative groups. Probing the changes that emerge in cognition as group …
Adaptive Decision Making in Dynamic Environments by Artificial and Biological Agents
NJ Wispinski - 2023 - era.library.ualberta.ca
The ability to adaptively respond to changing environments is a fundamental aspect of
intelligent behaviour. From catching a ball in motion to changing one's mind in the face of …
intelligent behaviour. From catching a ball in motion to changing one's mind in the face of …
Do artificial neural networks dream of understanding sentence comprehension? A preliminary study (¿ Sueñan las redes neuronales artificiales con entender la …
JP Martínez-Ramón, M Gil - Studies in Psychology, 2023 - journals.sagepub.com
Las redes neuronales artificiales (RNA) son un campo emergente con perspectivas
positivas y alentadoras. En educación, se postula que la atención y el rendimiento …
positivas y alentadoras. En educación, se postula que la atención y el rendimiento …
Brain Leitmotifs
R Traub, A Draguhn - Springer
A major problem of Neuroscience concerns the relationship between the activities of one or
more neurons and “something else”: something internal to the animal, such as actions …
more neurons and “something else”: something internal to the animal, such as actions …
[BOOK][B] Bridging State and Action: Towards Continual Reinforcement Learning
K Khetarpal - 2022 - search.proquest.com
The goal of this thesis is to improve the capability of AI agents to efficiently represent
knowledge and use it to plan and adapt to changes in their environment, through learning …
knowledge and use it to plan and adapt to changes in their environment, through learning …
The Paradox of Choice: On the Role of Attention in Hierarchical Reinforcement Learning
Decision-making AI agents are often faced with two important challenges: the depth of the
planning horizon, and the branching factor due to having many choices. Hierarchical …
planning horizon, and the branching factor due to having many choices. Hierarchical …