
## Data-Driven Revision of Conditional Norms in Multi-Agent Systems
Davide Dell'Anna, Natasha Alechina, Fabiano Dalpiaz, Mehdi Dastani, Brian Logan
Keywords: 
JAIR/2022/Proceedings/13683 - Data-Driven Revision of Conditional Norms in Multi-Agent Systems.pdf
Project URL: 

### Implementation
_Given the documentation given by the authors on the method, how much time investment would it be to re-implement the method from scratch?_

[1]

The authors provide a link to their implementation in the references (https://zenodo.org/records/5907522). In the readme they provide set up details, an overview of the structure and a description on what it contains + contact details. Comments are nice.

### Data
_Given the data description in the documentation, how much effort take to either: Find the same dataset the authors used, or similar datasets and defend the comparability, or acquire one from scratch?_

[1]

(1/1)

The authors use a traffic simulation and describe it in section 2, provide source code of it in their implementation, and state the scenario they use with parameter values in 4.1. 

### Configuration 
_Given the (hyper)parameters, including semantic parameters, of the method: How much effort would it take to acquire the algorithm configurations used for their results, and compare against their budgetary constraints?_

[4]

The configuration of DDNR is discussed at length in 4.1. A structured overview is not given, and the acquisition of x is not explained.

### Experimental Procedure
_Given the experimental set-up of the work, how difficult is it to set up a new experiment, similar to those presented in the original work, with the same procedure?_

[1]

The authors measure TP/FP/TN/FN and accuracy. The authors run 10 independent simulations. In figure 6 they present procentual change of these, but also mean and standard deviation as well as in table 5.

### Expertise
_How much effort would it take to acquire the expertise required to reproduce the work independently relying on the available documentation?_

[3]

Requries expertise on multi agent systems.
