An Adversarial Interpretation of Information-Theoretic Bounded Rationality
Authors: Pedro Ortega, Daniel Lee
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Here, we show that a single-agent free energy optimization is equivalent to a game between the agent and an imaginary adversary. The adversary can, by paying an exponential penalty, generate costs that diminish the decision maker s payoffs. It turns out that the optimal strategy of the adversary consists in choosing costs so as to render the decision maker indifferent among its choices, which is a deļ¬ning property of a Nash equilibrium, thus tightening the connection between free energy optimization and game theory. |
| Researcher Affiliation | Academia | Pedro A. Ortega and Daniel D. Lee School of Engineering and Applied Sciences University of Pennsylvania Philadelphia, PA 19104, USA {ope,ddlee}@seas.upenn.edu |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | No statement about open-source code availability or links to a code repository were found. |
| Open Datasets | No | The paper is theoretical and does not use datasets for training; thus, no information about public dataset availability is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for validation. |
| Hardware Specification | No | The paper is theoretical and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or training settings. |