Huang Ham
Biographic Data
| ID | 4601800 |
|---|---|
| NAME | Huang Ham |
| GIVEN NAMES | Huang |
| FAMILY NAME | Ham |
| SIGNATURE | HAM H |
| AFFILIATIONS | Princeton University |
| ORCID | 0009-0007-8630-3350 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Dual effects of dual-tasking on instrumental learning
How automatic is reinforcement learning (RL)? Here, using a recent computational framework that separates contributions from working memory versus RL during instrumental learning, we asked if taxing higher executive functions influences a putatively lower-level, procedural RL system. Across three experiments, we found that dual-tasking could indeed disrupt RL, even when isolating RL from working memory's contributions to behavior. These results s…
Teaching Recombinable Motifs Through Simple Examples
A hallmark of effective teaching is that it grants learners not just a collection of facts about the world, but also a toolkit of abstractions that can be applied to solve new problems. How do humans teach abstractions from examples? Here, we applied Bayesian models of pedagogy to a necklace‐building task where teachers create necklaces to teach a learner “motifs” that can be flexibly recombined to create new necklaces. In Experiment 1 ( N = 151)…
No prominent works on this page.
Dual effects of dual-tasking on instrumental learning
How automatic is reinforcement learning (RL)? Here, using a recent computational framework that separates contributions from working memory versus RL during instrumental learning, we asked if taxing higher executive functions influences a putatively lower-level, procedural RL system. Across three experiments, we found that dual-tasking could indeed disrupt RL, even when isolating RL from working memory's contributions to behavior. These results s…
Teaching Recombinable Motifs Through Simple Examples
A hallmark of effective teaching is that it grants learners not just a collection of facts about the world, but also a toolkit of abstractions that can be applied to solve new problems. How do humans teach abstractions from examples? Here, we applied Bayesian models of pedagogy to a necklace‐building task where teachers create necklaces to teach a learner “motifs” that can be flexibly recombined to create new necklaces. In Experiment 1 ( N = 151)…
Artificial Intelligence (2 works) · Computer Science (2 works) · Artificial Intelligence (1 works) · Cognition (1 works) · Cognitive psychology (1 works) · Cognitive science (1 works) · Dual (grammatical number) (1 works) · EEG and Brain-Computer Interfaces (1 works) · Epistemology (1 works) · Executive functions (1 works)