## Lazy Agents: A New Perspective on Solving Sparse Reward Problem in Multi-agent Reinforcement Learning
Boyin Liu, Zhiqiang Pu, Yi Pan, Jianqiang Yi, Yanyan Liang, D. Zhang
Keywords: 
ICML/2023/Proceedings/25199 - Lazy Agents: A New Perspective on Solving Sparse Reward Problem in Multi-agent Reinforcement Learning.pdf
Project URL: nan

### 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]

1. Implementation is given and seems reasonable and has comments

### 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]

(2/2)

1. Environments are described in the Appendix and are contained in the code-base as well.

### 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?_

[5]

1. Hyperparameters are rather informally stated +2
2. Not clear how hyperparameters have been obtained or what are the hyperparameters of the
   baselines +2


### 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]

1. Performance metric return is very standard but it is not mentioned what kind of confidence intervals are being used +1 (aggregation)

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

[4]

Code seems fine so it should be possible without huge efforts