From: Conrad Schecker <redacted>
Date: Mon, 9 Feb 2026 09:23:46 +0000 (+0100)
Subject: fix typos
X-Git-Url: https://git.conrad-schecker.de/?a=commitdiff_plain;p=fj-contracting.git

fix typos
---

diff --git a/README.md b/README.md
index 4a3d7a4..05718b2 100644
--- a/README.md
+++ b/README.md
@@ -1,27 +1,27 @@
-This is an implementation of the FJ contracting problem using the Rust programming languange.
-It was used for making experiments about the performance of greedy algorihms described in the paper "Contract Design in Opinion Formation Games".
+This is an implementation of the FJ contracting problem using the Rust programming language.
+It was used for making experiments about the performance of greedy algorithms described in the paper "Contract Design in Opinion Formation Games".
 
 ## Build and Run
 
 The easiest way to run this application is to use [Cargo](https://doc.rust-lang.org/cargo/getting-started/installation.html), the package manager for Rust.
-After cloning the repository, the project can be built using 
+After cloning the repository, the project can be built using:
 ```sh
 cargo build
 ``` 
 For performance reasons, using the `--release` flag is highly recommended in order to enable compiler optimizations.
 
 There are two main CLIs in this project.
-- `fixed_graph` for simulations on a fixed graphs with varying numbers of influencers.
-- `hrg` for simulations on hyperbolic random graphs (or any set of graphs graphs).
+- `fixed_graph` for simulations on fixed graphs with varying numbers of influencers.
+- `hrg` for simulations on hyperbolic random graphs (or any set of graphs).
 
-Additionally, there is a binary `bench` which provides a testing environment for identifying bottlenecks of the implementation.
+Additionally, there is a binary `bench` that provides a testing environment for identifying bottlenecks in the implementation.
 All CLIs provide additional information about the required parameters using the `-h` flag.
-Note that you can also build and run the CLIs directly using cargo, e.g., by 
+Note that you can also build and run the CLIs directly using cargo, e.g., by:
 ```sh
 cargo run --release --bin fixed_graph -- -h
 ```
 
-There is an extensive documentation that can be built using 
+There is extensive documentation that can be built using:
 ```sh
 cargo doc --no-deps
 ```
@@ -32,7 +32,7 @@ As described in the paper, simulations were performed on several graphs from the
 We provide a shell script that invokes their CLI `genhrg` for batch generation of hyperbolic random graphs of the same size.
 Details can be found in the comments of the script (`./generate_hrg.sh`).
 
-Once all necessary hyperbolic random graphs have been generated, the simulations can be started with the following command
+Once all necessary hyperbolic random graphs have been generated, the simulations can be started with the following command:
 ```sh
 mkdir -p ./results/
 
@@ -42,13 +42,13 @@ This will run the simulations (with 128 repetitions) for graphs with sizes n = 2
 The necessary graphs have to be in the `./graphs/` directory.
 
 You can also store fixed graphs in that directory.
-For example, if you want to run the simulation on `socfb-Caltech36.mtx` in the directory `./graphs/`, you can run simulations by the following command:
+For example, if you want to run the simulation on `socfb-Caltech36.mtx` in the directory `./graphs/`, you can run simulations with the following command:
 ```sh
 mkdir -p ./results/
 
 cargo run --release --bin fixed_graph -- --input-file ./graphs/socfb-Caltech36.mtx --output-directory ./results/ --action-set-generator GeometricFirstvalueZero --action-set-size 64 --influencer-selector MostInfluential
 ```
-This will generate an action set using `GeometricFirstvalueZero(64)`, and select most influential agents as influencers.
+This will generate an action set using `GeometricFirstvalueZero(64)`, and select the most influential agents as influencers.
 By default, there will be 2 to 12 influencers, and for each influencer count, 128 repetitions will be made.
 
 Note that simulations take some time already on relatively small graphs with ~1000 nodes.