
## Maximisation of Admissible Multi-Objective Heuristics
Patrik Haslum, Ryan Xiao Wang
Keywords: 
JAIR/2023/Proceedings/14861 - Maximisation of Admissible Multi-Objective Heuristics.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?_

[10]

No implementation given.

### 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?_

[4]

(1/1)

The authors use a benchmark of MO planning problem by Geißer et al (citation). No other details.

### 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?_

[1]

No parameters stated.

### 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?_

[2]

The authors evaluate the methods in single runs over cumulative frequency, but this is not explained.

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

[5]

Requires expertise on MO heuristics.
