
## The Importance of Non-Markovianity in Maximum State Entropy Exploration
Mirco Mutti, Riccardo De Santi, Marcello Restelli
Keywords: 
Award: Outstanding Paper
ICML/2022/Proceedings/962 - The Importance of Non-Markovianity in Maximum State Entropy Exploration.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?_

[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?_

[6]

(2/2)

The authors use simulated environments River Swim and 3State which they provide citations on and describe, and provide parameter values. No implementation given.

### 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?_

[10]

There are no parameter values discussed in sec 6, although there are parameters defined in the paper.

### 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 prsent the results over 100 runs and state the average with 95% CI. Metrics are entropy but not each is clear straight away clear. Data split not applicable. 

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

[6]

Requires expertise on Markovian stochastic policies.
