SoC Ideas Your Own Ideas 2014

From The Battle for Wesnoth Wiki

This page is related to Summer of Code 2014
See the list of Summer of Code 2014 Ideas

This is a Summer of Code 2014 Idea


Other: Your own ideas

Page for the idea: SoC_Ideas_Your_Own_Ideas_2014

Suggested skills: C++ (depends on the project).

There are 9 submitted student proposals for this idea

Dugi - Campaign Wizard

I've seen on the forums that people frequently ask for campaign wizards and such and when they're told that there is no such thing, they struggle usually with the basics like writing a proper _main.cfg file. There is a project named Eclipse Java plugin, but it's not a part of wesnoth, only a few people know about it and it is basically just a text editor adapted to work with WML. This project is to make a campaign wizard, incorporated into the game, that would allow creating simpler campaigns in an intuitive way, without having to read or write source codes.

The idea is to create a campaign making GUI that would be accessible from the map editor or some other menu, and would allow making campaigns without writing any codes, just clicking and writing some dialogues, unit names and such. It wouldn't allow doing all the things that can be done with WML, just the more common things.

It would contain several windows or tabs, one for the entire campaign's properties (setting up the basic properties), one for the scenarios (setting up the basic properties, like assigning maps, sides' properties, then adding commonly used events) and something for adding custom units (basic properties, assigning images to attacks and animations).

It would need to use slightly different data structures than usual wesnoth because campaigns need including files and macros, preprocessor defines and similar things that are usually parsed out when reading the files. I think that they could be created through inheritance and a few modifications (especially a special tag for macros and a property to make it depend on difficulty).

The map editor can do a plenty of things around scenarioWML, so it might be used to create scenarios after some editing, but at least some sort of ActionWML editor would need to be added (supporting basic tags like message, creating units, killing units, moving units).

This is what the main window of the campaign editor might look like (sorry for not caring much about the layout's appearance, but that's not the point): 1Y6Og6S.png

Further expansions (if time remains or to be done in another summer) may include support for ifs, variables and objects in ActionWML, AMLA, custom abilities and weapon specials in UnitWML, maybe possible alternative scenario paths.
See Dugi's Campaign Wizard for more information.

GoblinThing Campaign Wizard


Due to my particular skill set, working on the eclipse plugin (the UMC editor) would be ideal. Once I manage to acquire a copy of the source code, the project will probably go something like this:

1) (main task) check the wizards that are supposed to exist within the plugin. Make any modifications necessary to keep it up-to-date with WML, then make any changes, additions, or modifications that might be useful to the users. Wizards should include a scenario wizard and campaign main wizard, as these are the most painful to build by hand. Additional components may include a unit wizard, event wizard, and anything else I can think up. Unfortunately, I can't be more specific at this time.

2) (additional task) Check with the original author (Timeotei, I beleive,) and see if there are any things he wanted to include from GSoC 20(11? 12?) and try to implement them. It would be nice to contribute to the original vision.

3) (additional task) Once all other possible tasks have been completed, start a forum thread in the "wml" section and see if anyone has a unique/much needed addition. If they do, I can work on that...

4)...and if they don't, ask the devs for more work. IF my proposal is selected, I see GSoC as a job, and will work like a rabid horse.

I'm still working at convincing eclipse to load the UMC editor properly, and will post additional (much-needed) details as soon as I can.

Thanks for reading,


See GoblinThing Wizard for more information.

TODO: Copy this page and write "your name - proposal title" in this h4 section

TODO: Write a small (1-4 sentences) description of your proposal here.

TODO: Add more first-level sections to detail your proposal
See GSoCMindblank for more information.

Improve Random Map Generator

The aim of this proposal is to create better random-generated maps for singleplayer and multiplayer game using new elements and options

Using different "biomas" in the same map (not only desert for example) to make more "unique" scenarios, also, including other elements like peninsulas so the general form of the map changes
See Improve Random Maps for more information.

AI: Improve AI by implementing global attack/retreat decision

Page for the idea: SoC_Ideas_AI_Global_strategy

The Wesnoth AI works by making local decisions about moves and attacks. Teach it to determine if it's worth to fight offensively or defensively in a given situation.

There are 5 submitted student proposals for this idea

Aditya Pande - Global AI for Battle of Wesnoth

I propose to implement global AI using a combination of idea of Quiescence search on game tree with alpha beta pruning along with a few heuristics to make it possible to actually solve this complex game. Also this approach requires an evaluation scheme for the same.

The idea of using Quiescence search here is different than that in chess engines. Here my idea is to reduce the average branching factor for each choice made by considering the ones which do not affect the game drastically (hence called quiet moves). In this case the braching factor for a unit can be given by

braching factor=Number of attacking moves + Number of Acquire village moves + 2

The 2 represent all Quiet moves based on retreat or charging forward towards enemy. As the quiet moves above do not affect the game drastically they shall be decided based on heuristics and here I plan to only consider the greatest retreat/charge.

The idea behind my approach is based on "Wesnoth can be treated much like a continuous game, because many positions tend to be very similar to each other. Additionally, unlike discrete board games, it is not common that a very small wrong move in Wesnoth is disastrous."

The aim of the whole approach is to simplify the game complexity using few heuristics and then use approach of negamax to select a good overall global move(not the best because of the simplication done) . Also the number of attacking moves and number of acquire village moves has to be reduced to actually keep the problem solvable. (Read all the heuristics for the same in Technical description).

I also plan to divide the whole problem into independent parts whenever possible. Let me give an example, lets say that the AI is under attack on 2 fronts but there is (currently) no relation between the 2 as to say that the AI units involved can't interact(i.e they are too far and can't 'get close' to each other in next turn). My idea is that by doing such division and focusing on solving each problem individually sharply reduces the complexity of the problem.

Lastly I plan to adopt some ideas from Fuzzy Logic, FSM and Behaviour trees to improve the current model I propose.
See Aditya Pande Global AI for more information.


I would like to improve the AI by implementing Global attack / retreat decision.

Elements : Anything around the unit that can cause a change to the behavior

Behavior : Determine what the enemy is going to do based on the elements.

Deliberation : Does the best move depending on the behavior previously set .

To do so I will use probality theory to determine what is best move to do.
See Improve AI for more information.

Arveanor Global AI

Give an ai player a set of potential objectives to pursue such as taking a village, killing an enemy, defending a village etc. Also give each ai different behavior modes based on the information they have access to. i.e. fight aggressively, fight defensively, fight cautiously etc. The ai would, depending on it's current behavior mode pursue the objectives more or less rigorously depending on how they align with the current behavior.

The behaviors and objectives would not necessarily mix strongly with recruitment, however a similar system to what would analyze which behavior to be used would also be able to inform recruiting patterns. Obviously certain unit types and a large amount of certain terrain hexes give good reason to favor certain units in recruitment, of course gaining vision and taking outlying villages (i.e. AI global objectives) would play into recruitment in terms of recruiting faster units.
See SoC2014 arveanor ai for more information.

Kevin Xi - AI: Improve AI by implementing global attack/retreat decision

A rule-based expert system style solution utilizing dynamic programming to make decisions
See SoC2014 kevin AI for more information.

See SoC2014 vorobeez AI for more information.

See Jchb AI Global Strat for more information.

neonosos - Improve AI by global world analysis

My goal is to contribute Wesnoth AI by improving AI players with global-analysis skill. This skill makes AI players able to not only react on local impulses (such as attack or presence of another player), but also to make deeper-planned strategies.

Economical aspect
The AI player should be able to decide which enemy to attack according to his economical needs. It means, that if AI player needs gold, he should attack player with high gold resources.
War-strategy aspect
AI player should not attack if it's not appropriate. Why to attack player, that is much stronger than the AI? Maybe some kind of indirect (for example economical, diplomatic) attack would be more appropriate.
Planning for future aspect
Should I attack the nearest enemy's village? Why not to attack the further one, cutting of the escape from the nearest village?

See Neonosos for more information.

Daniwa: Improve the AI's Attack and Retreat decisions.

Abstract: Implement a process that would allow the AI to make correct decisions in regards to attack and retreat. It will be based off probability focused on current metagame habits.

Proposal: The focus of my implementation is not on outputting the optimal result in every case but instead will aim at mirroring a player like decision. The goal for this is to foster and develop good game decision making in new players and prevent bad habits. Ideally, the AI should act correctly but unpredictably (which is technically impossible) and be able to be a training aid.
See SOC2014 Daniwa Ai for more information.

Zubin Kapaida: Improve AI by implementing global attack/retreat decision

I believe that the key to making a good AI bot is to keep your ideas clear and simple. One must evaluate the gravity of the situation using the given parameters and accordingly act offensively or defensively.

Sometimes it is more beneficial to risk one unit’s death or even sacrifice a few and perform the attack, the tricky part is to figure out when. In this game “Battle of Wesnoth” several factors affect the decision making like terrain, time of day (i.e. day / night), special abilities, enemy units’ status etc.

Positioning is a crucial part, ideally we should try to position every unit such that it has backup from other units and is away from critical danger, also positioning in terrain that would support maximum defense if ideal. Next we must try to exploit the enemies weakness, e.g. if the enemies unit has no defense in range, then we should attack that unit with heavy range units. Also while attacking we must try to surround the enemy from multiple directions and then synchronize the attack.

For implementation I propose use different parameters like aggression, depth etc. Here aggression parameter would specify how much the AI values its own units as opposed to that of the enemies. Depth parameter indicates the number of units that will attack a single opponent unit. protect_leader (radius) parameter, it is used to target any enemy unit which comes within the specified radius around the leader, and many others will be needed.

The value of aggression will determine whether to play offensively or to retreat. Next I propose the use of decision tree to determine the value of aggression. The decision tree will be a binary tree and in each node we check some condition like terrain, time of day etc. which affects our strategy. So we start from the root node and after validating all the conditions we end up on a leaf node. The value of aggression will be determined on the basis of the leaf node we end up on.

As mentioned earlier positioning is very important. Positioning of units is different for aggressive and defensive approaches. To plan out the positioning we will use threat map. A threat map is a 2D array which describes the level of danger on every position. While building a threat map, the positioning of the enemy units, type of units and other factors are taken into account.
See SoC2014 Zubin AI for more information.

ykanarev - AI task implementation

TODO: Write a small (1-4 sentences) description of your proposal here.

TODO: Add more first-level sections to detail your proposal

TODO: Set the proper Category in the top of the page ([[Category:XYZ]]), to match the one you'd like to apply for, from the list on the main summer of code page (e.g.: [[Category:SoC_Ideas_AI_Global_strategy]]). Otherwise your idea will be marked as a new one.
See YKanarev AI impl for more information.

Additional Information

You're welcome to propose your own ideas to Wesnoth's developers.

Whom to ask about this

Mail wesnoth-dev mailing list, try to find a developer interested in your idea.

This page was last edited on 14 February 2014, at 22:16.