Causality

[AAAI20] Theory-based Causal Transfer: Integrating Instance-level Induction and Abstract-level Structure Learning

[CogSci19] Decomposing Human Causal Learning: Bottom-up Associative Learning and Top-down Schema Reasoning

Transfer learning is fundamental for intelligence; agents expected to operate in novel and unfamiliar environments must be able to transfer previously learned knowledge to new domains or problems. However, knowledge transfer manifests at different …

[CogSci18] Human Causal Transfer: Challenges for Deep Reinforcement Learning

Discovery and application of causal knowledge in novel problem contexts is a prime example of human intelligence. As new information is obtained from the environment during interactions, people develop and refine causal schemas to establish a …

[VR2018] Spatially Perturbed Collision Sounds Attenuate Perceived Causality in 3D Launching Events

When a moving object collides with an object at rest, people immediately perceive a causal event: i.e., the first object has launched the second object forwards. However, when the second object's motion is delayed, or is accompanied by a collision …