Beginning in mobile development and willing to make Bouftools great again by finding a new concept. Dofus Retro doesn't have in game XP and drop simulation, I wanted to develop a tool where players could access this feature easily.

Steps

Seeking data & formula

First step was to access monster base XP and the formula, hours of putting internet upside down to find tracks and assumption to finally reach a correct simulation. Many in game tests were also necessary to make sure of the correctness.

What I did: Match multiple sources of old Dofus data and elaborate scripts to gather them regularly.

Probability

With the help of Florent Huylenbroeck, we elaborate the computation of drop probability for one monster at a time.

Single: Compute the probability of one player considering his prospection, item quantity available and his place in the team.
Team: Compute the probability of the whole team and display the highest percentage to get a certain quantity.

Steps

Framework & algorithms

First step was to find a suitable framework and algorithms to detect cards one by one and accurately.

Difficulties: Create a dataset and correct training routine, compare and experience different models.
Solutions: Consider cards artworks for training, chose Darknet & Yolo because of the efficiency and plenty of documentation available.

Embedded system

Once the base model was accurate enough, I tried to adapt it on microcomputer like Raspberry Pi in order to easily add it to the future machine design.

Difficulties: Find a correct balance between speed and accuracy. Convert the Yolo approach into a library designed for embedded systems.
Solutions: Export the detection on a private server for privacy and efficiency.

Design the machine

Finally, the design of the machine is the last step that I'm currently experiencing in order to merge every part of the project.

Difficulties: Elaborate 3D models and check possible patents. Find a balance between speed and card respect.
Solutions: Open source 3D robot arm and suction cup to manipulate the cards.

Beginning in web development, I wanted a unique challenge in order to mix different disciplines. Data scraping, packet analysis, OCR and botting were really interesting to elaborate reverse engineering and snoop behind the scene of a video game.

Steps

OCR & Macro

First iteration was to configure macros to connect my character in the game and browse merchants NPC. Gathering prices by training an OCR based on Dofus font and an errata list to correct possible wrong interpretations.

Cons: Unreliable macro, only one server available, time consuming and Dofus changed font style
Next step: Find an existing API allowing to gather prices

Bot socket

Next iteration was a technological watch to gather in game data. A jump into the dark side made me seek developers behind a bot socket. After a little talk about Bouftools, we agreed for a free use of their program and no advertising from me.

Pros: Reliable, quick and multiple servers at once
Cons: Need to subscribe accounts

Last updates

After some reverse engineering and game updates, I found some solutions.

• Ankama reduced number of merchants (less move from the bot)
• High level items still available if asked to the non subscriber zone merchant
• No need to subscribe accounts anymore

We had to develop two AI, one random (Random captain Iglo) and one more developed (Eat my fish stick). Those two AI must work with both turn by turn and simultaneous play mechanics. I'm going to explain only the non random.

Complete report

Steps

Message passing & rules

Submarines have access to all actions from each other through messages passing on a stream . At the beginning of the game they don't know ennemies position and can fire mines, missiles and sonar to locate (more or less accurately) enemies. The game ends when only one submarine remains.

AI code

AI logic

Trust list: Each submarine got a list with enemies coordinates and a list with a trust factor (0, 1 and 2 from trusty to untrusty) depending of the sonar quality and the progress of the game.
Analyze intents: Depending of ennemie's actions, each submarine keeps track of health, landing mines and moves. For instance, if one submarine is hurt by a mine, everybody is aware of this event. Depending of damages taken, all submarines update their trust list and define a prey.