Generalizing to generalize: Humans flexibly switch between compositional and conjunctive structures during reinforcement learning
NT Franklin, MJ Frank - PLoS computational biology, 2020 - journals.plos.org
Humans routinely face novel environments in which they have to generalize in order to act
adaptively. However, doing so involves the non-trivial challenge of deciding which aspects …
adaptively. However, doing so involves the non-trivial challenge of deciding which aspects …
Learning from different perspectives for regret reduction in reinforcement learning: A free energy approach
Reinforcement learning (RL) is the core method for interactive learning in living and artificial
creatures. Nevertheless, in contrast to humans and animals, artificial RL agents are very …
creatures. Nevertheless, in contrast to humans and animals, artificial RL agents are very …
Local and soft feature selection for value function approximation in batch reinforcement learning for robot navigation
This paper proposes a novel method for robot navigation in high-dimensional environments
that reduce the dimension of the state space using local and soft feature selection. The …
that reduce the dimension of the state space using local and soft feature selection. The …
[PDF][PDF] Multiagent Reinforcement Learning for Traffic Signal Control: a k-Nearest Neighbors Based Approach.
The increasing demand for mobility in our society poses various challenges to traffic
engineering, computer science in general, and artificial intelligence in particular. As it is …
engineering, computer science in general, and artificial intelligence in particular. As it is …
Subgoal Discovery Using a Free Energy Paradigm and State Aggregations
A Mesbah, R Hosseini, SP Shariatpanahi… - arXiv preprint arXiv …, 2024 - arxiv.org
Reinforcement learning (RL) plays a major role in solving complex sequential decision-
making tasks. Hierarchical and goal-conditioned RL are promising methods for dealing with …
making tasks. Hierarchical and goal-conditioned RL are promising methods for dealing with …
Soft dimensionality reduction for reinforcement data clustering
The standard Euclidean distance considers equal contributions for all features of each data
sample pair when computing the similarity matrix, while different features of real-world …
sample pair when computing the similarity matrix, while different features of real-world …