Modeling Subjective Experience-Based Learning under Uncertainty and Frames
Authors: Hyung-il Ahn, Rosalind Picard
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our analysis and simulations of two-armed bandit tasks present that the task domain (underlying outcome distributions) and framing (reference point selection) influence experienced utilities and in turn, the subjective discriminability of choices under uncertainty. Experiments demonstrate that subjective discriminability improves on objective discriminability by the use of the experienced-utility function with appropriate framing for a given task domain, and that bigger subjective discriminability leads to more optimal decisions in learning under uncertainty. |
| Researcher Affiliation | Collaboration | Hyung-il Ahn IBM Research 650 Harry Road, San Jose, CA 95120 hiahn@us.ibm.com Rosalind W. Picard MIT Media Lab 75 Amherst St, Cambridge, MA 02139 picard@media.mit.edu |
| Pseudocode | No | The paper describes computational models and decision rules mathematically but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any statement or link indicating the public availability of its source code. |
| Open Datasets | No | The paper describes simulated bandit tasks with Gaussian outcome distributions, but it does not specify or provide access information for a publicly available dataset. |
| Dataset Splits | No | The paper describes an exploratory trial phase within its bandit task simulations but does not specify train/validation/test dataset splits in the conventional sense for hyperparameter tuning or model selection. |
| Hardware Specification | No | The paper does not provide specific details regarding the hardware specifications used for running its experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers needed to replicate the experiments. |
| Experiment Setup | Yes | Subplots (a), (b) and (c) in Figure 4 show the simulation results on how the reference point selection (framing) influences subjective discriminability on different domains... for a decision maker employing a subjective value function (experienced-utility (EU)) function with shape parameters a = 0.8, b = 0.5, λ = 2.5. |