An Ambiguity Aversion Model for Decision Making under Ambiguity
Authors: Wenjun Ma, Xudong Luo, Yuncheng Jiang
AAAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Some insightful properties of our model and the validating on two famous paradoxes show that our model indeed is a better alternative for decision making under ambiguity. and Finally, we will valid our model by solving two famous paradoxes. |
| Researcher Affiliation | Academia | 1 School of Computer Science, South China Normal University, Guangzhou, China. 2 Institute of Logic and Cognition, Department of Philosophy, Sun Yat-sen University, Guangzhou, China. |
| Pseudocode | No | The paper defines concepts and provides mathematical formulas but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any statement about making its source code available or providing a link to a code repository. |
| Open Datasets | No | The paper validates its model using well-known conceptual paradoxes (Ellsberg and Machina) which are scenarios rather than traditional datasets with explicit access information. |
| Dataset Splits | No | The paper does not describe dataset splits (e.g., training, validation, test) as it focuses on theoretical model validation against conceptual paradoxes rather than empirical data evaluation. |
| Hardware Specification | No | The paper does not mention any specific hardware specifications used for experiments or computations. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers. |
| Experiment Setup | No | The paper focuses on theoretical model development and mathematical analysis of paradoxes, and therefore does not include details on experimental setup, hyperparameters, or training configurations. |