LuaAI
Wesnoth provides the functionality to both access and define all types of AI components using Lua. Instructions for using these components to customize the default AI and to create custom AIs are explained on other pages. See Wesnoth AI for a summary of the available documentation. This page is a reference guide to the Lua AI functions, variables and component syntax.
Contents
Lua AI Functions
The code of custom Lua candidate actions (CAs) has access to the ai table. This is a Lua table containing functions for getting information about the game state and for executing AI moves. Together with the other Wesnoth Lua functions they can be used in the CA evaluation and execution functions to code the desired AI behavior.
ai Table Functions Returning Game State Information
The ai table contains a large number of functions returning game state information. Some of those are simple scalar values which are self-explanatory, while others can be tables with many elements and complex structure. We will not show the structure of all these tables here. If you need to know the exact structure of such a table, use the method described below for accessing the AI tree.
Functions Returning Aspect Values
The contents of many of the AI aspects can be read using ai table commands of the form
- ai.get_<aspect_name>(), for example
- ai.get_aggression()
- ai.get_caution()
Note that this returns the result of the aspect evaluation given the game state at the time of the last invalidation of the aspect, not its definition. For example, ai.get_avoid() returns the list of avoided hexes, rather than the Standard Location Filter used to find them, and dynamic Lua aspects return the function evaluation result, not the function itself.
The full list of functions returning aspect values is
Functions returning scalar values (numbers, strings or booleans): ai.get_aggression() ai.get_attack_depth() ai.get_caution() ai.get_grouping() ai.get_leader_aggression() ai.get_leader_ignores_keep() ai.get_leader_value() ai.get_number_of_possible_recruits_to_force_recruit() ai.get_passive_leader() ai.get_passive_leader_shares_keep() ai.get_recruitment_ignore_bad_combat() ai.get_recruitment_ignore_bad_movement() ai.get_scout_village_targeting() ai.get_simple_targeting() ai.get_support_villages() ai.get_village_value() ai.get_villages_per_scout() Functions returning tables: ai.get_attacks() ai.get_avoid() ai.get_leader_goal() ai.get_recruitment_pattern()
Functions Returning Other Game State Information
- ai.get_targets(): Get the AI targets. See below for details.
- ai.side: side number of the AI
- ai.suitable_keep(unit): This returns the location of the closest keep to the unit passed as argument. Note that this returns the x and y coordinates of the keep as two separate arguments, so it needs to be called as
local x, y = ai.suitable_keep(unit).
Finally, the following functions related to move maps (tables that relate the current positions of units and the hexes they can move to) also exist:
- ai.get_new_dst_src()
- ai.get_new_enemy_dst_src()
- ai.get_new_enemy_src_dst()
- ai.get_new_src_dst()
- ai.is_dst_src_valid()
- ai.is_enemy_dst_src_valid()
- ai.is_enemy_src_dst_valid()
- ai.is_src_dst_valid()
- ai.recalculate_enemy_move_maps()
- ai.recalculate_move_maps()
If you need to know what they do and the exact structure of their return values, use the method described below for accessing the AI tree.
ai Table Functions for Executing AI Moves
For all functions below, units (unit, attacker, defender) can be passed either as a unit object in a single variable, or as two parameters specifying the unit's x and y coordinates. For functions taking more than one unit as arguments, it can also be a mix of the two.
- ai.attack(attacker, defender, weapon, aggression): Execute attack by attacker against defender. If weapon is provided, it is the number of the weapon to be used (count starts at 1, not 0, as always in Lua), otherwise choice of the weapon is left to the AI engine. If aggression is provided, it is used to influence the choice of the best weapon, Obviously, this only makes sense if this choice is left to the engine, that is, if weapon is set to either 'nil' or '-1'.
- ai.move(unit, to_x, to_y): Execute partial move of unit to hex (to_x, to_y). Partial move means that the unit keeps whatever movement points it has left after the move.
- ai.move_full(unit, to_x, to_y): Execute full move of unit to hex (to_x, to_y). Full move means that the unit's movement points are set to zero at the end of the move.
- ai.recall(unit_id, x, y): Recall the unit with id unit_id. An optional recruit location can be given in x and y. If the location is omitted, a suitable hex is automatically chosen by the AI engine.
- ai.recruit(unit_type, x, y): Recruit a unit of type unit_type. An optional recruit location can be given in x and y. If the location is omitted, a suitable hex is automatically chosen by the AI engine.
- ai.stopunit_attacks(unit): Remove remaining attacks from unit. This is equivalent to setting
attacks_left=0. - ai.stopunit_moves(unit): Remove remaining movement points from unit. This is equivalent to setting
moves=0. - ai.stopunit_all(unit): Remove both remaining attacks and remaining movement points from unit.
- ai.synced_command(command, x1, y1): Execute the specified Lua command in a replay and MP safe way. command is a string containing the Lua code and (x1,y1) is an optional map location that is the only allowed external variable used in the code string (specified as Lua variables x1 and y1).
The following functions are available for checking whether a planned AI move is possible. This is useful in order to prevent an aborted execution of a move, which might result in some or all of the remaining moves to be aborted by the AI due to a blacklisted candidate action.
- ai.check_attack()
- ai.check_move()
- ai.check_recall()
- ai.check_recruit()
- ai.check_stopunit()
- ai.check_synced_command()
These check functions take the same arguments as the respective AI action functions. They return a Lua table which looks something like the following for a successful check
{
gamestate_changed = false,
ok = true,
status = 0
}
and like this for an unsuccessful check
{
gamestate_changed = false,
ok = false,
status = 2008
}
Notes:
- status is the error code returned by the AI engine in case of an unsuccessful code. The error string for a given error code can be found in file src/ai/actions.hpp.
- The move execution functions return the same table, with the only difference being that gamestate_changed is 'true' in case the execution resulted in a change of the game state (even if the move was only partially successful).
Lua AI Variables — Persistence
When Creating Custom AIs in Lua, it is sometimes necessary to transfer information between the evaluation and execution functions of the same candidate action (CA) or between CAs. It might also be necessary to have this information persist from turn to turn and across save/load cycles. This could, in principle, be done using WML variables, but depending on the type and amount of information, that could be awkward and/or inconvenient to do in practice.
The Wesnoth AI therefore includes a field called data which is automatically added to the internal AI context. The evaluation and execution functions of Lua candidate actions have access to this field if the third (optional) variable is passed to them. Assuming this variable is called self, the field is accessed as self.data.
When saving a game, the save routine finds this field, converts it to a config and stores its content in readable format in the save file. When the scenario gets loaded back, the engine code injects the data back into the AI context. Note that, in order for this to work, all content of data needs to be in WML table format. Other format content can also be used during an AI turn, for example to pass it between the evaluation and execution functions of the same CA, but it is lost when saving the game.
Dynamic Lua Aspects
It is possible to define aspects using Lua. These can be either static or dynamic, that is, their value can change depending on the game state. We demonstrate this here with a few examples.
First, as simple example of defining the aggression aspect statically in Lua:
[aspect]
id="aggression"
engine="lua"
value="0.765"
[/aspect]
There is, of course, no advantage of this over simply defining the aspect in WML, we simply show it for completeness and for the syntax. An example of defining aggression dynamically so that it increases slowly from turn to turn is
[aspect]
id=aggression
engine=lua
code=<<
local value = wesnoth.current.turn / 10.
return value
>>
[/aspect]
Note the difference between the value and code attributes in the two examples.
The advancements Aspect
A slightly more elaborate example, using the advancements aspect, is given below. This aspect is different from others in that it can be used with a function advance(x, y), where (x, y) is the current location of the unit about to advance. You can then use wesnoth.get_unit(x, y) to retrieve the unit object itself. For example, the following code advances the unit with id 'Bob' to a swordsman (assuming here that this unit is a spearman), while all other spearmen are advanced to javelineers.
[ai]
[aspect]
id=advancements
engine=lua
code=<<
function advance(x, y)
local unit = wesnoth.get_unit(x, y)
if (unit.id == 'Bob') then
return 'Swordsman'
else
return 'Javelineer'
end
end
return advance
>>
[/aspect]
[/ai]
Note that this aspect only affects AI units while they are attacking. When a defending unit advances, it is still decided randomly. That is because Wesnoth's design does not allow the AI to make out of turn decisions.
Goals and targets
It is also possible to define AI goals and targets in Lua. This is, however, somewhat inconvenient and we generally recommend using the [goal] tag with WML Standard Unit Filters (SUFs) or Standard Location Filters (SLFs) instead. That is much more versatile and it makes no difference to the AI behavior whether the goals are defined using WML or Lua.
The only time that defining goals in Lua might be advantageous is if one wants to use goals with dynamic values, such as in this example, where one goal has a constant value, while the other's value increases from turn to turn.
[goal]
name=lua_goal
engine=lua
code = <<
local turn = wesnoth.current.turn
local targets = {}
targets[1] = { value = 2, type = 2, loc = { x = 5, y = 6 } }
targets[2] = { value = turn * 2 , type = 2, loc = { x = 4, y = 9 } }
return targets
>>
[/goal]
As you can see, the return value must be an array containing the targets. Each target must contain three fields:
- value: The value of the target, equivalent to that defined for WML goals
- loc: A table with attributes x and y defining the target's location. This is one of the disadvantages with respect to the WML syntax. Each goal needs to be defined individually by its coordinates. The use of SUFs and SLFs is not possible.
- type: A number defining the type of the target. File src/ai/default/contexts.hpp defines the available types as
enum TYPE { VILLAGE, LEADER, EXPLICIT, THREAT, BATTLE_AID, MASS, SUPPORT };
User-defined targets should usually be given type = 2 for target and target_location type targets, and type = 3 for protect_* type targets. This corresponds to EXPLICIT and THREAT targets (the third and fourth in the enum list, with counting starting at 0).
Notes:
- This code is parsed by the Lua engine and the targets are available to any engine.
- Targets can be read in Lua using ai.get_targets()
- This produces a Lua array like the one above, with one element for each hex that was found as a target (even if SUFs or SLFs were used in WML).
- The table also includes all the automatically generated targets.
Lua AI — Legacy Methods
The recommended method of using cutom Lua AI functionality is described at Creating Custom AIs. A variety of alternative older methods also still exist. There should be few, if any, situations in which using these methods is advantageous, but for completeness they are described on a separate page.
The methods include:
- Lua stage: There should not be anything that can be done with the Lua stage that cannot just as easily be done with the main_loop stage.
- Lua engine: With the new type of Lua candidate actions, it is not necessary any more to define a Lua engine. This is only needed for the old-style CAs.
- The old syntax for defining Lua candidate actions: There is no advantage of using the old syntax over the new one. On the contrary, among other things the old method requires the separate definition of a Lua engine, which is unnecessary with the new method.
- Preload event: It is not necessary to set up a preload event any more (the one possible exception might be in order to set up a debug testing mechanism).
- Behavior( sticky) candidate actions: These are Lua CAs which attach directly to specific units. They could, in principle, still be useful. However, using the new syntax for Lua CAs with a condition to filter for specific units is usually simpler. Several of the Micro AIs demonstrate how to do so.
Debug access to the AI tree
[ Todo: this section is currently just a collection of content from other pages. Needs to be cleaned up and updated. ]
debug_utils from Wesnoth Lua Pack is a very powerful tool to analyze what is going on when something is not working as expected. It can be used to display the content of essentially any Wesnoth Lua data structure. As an example, the following command:
debug_utils.dbms(ai, false, "variable", false)
shows all the default Lua AI functions -- assuming that the ai variable has been initialized.
Now it is possible to reload candidate actions on-the-fly, meaning that each new turn will reload the actual file from the hard-drive, if Wesnoth is launched with the --debug-lua launch argument. This works only with external candidate actions. Candidate actions defined in the engine inside the config file of the scenario will not be reloaded. The purpose for this is easy debugging. Now the developer does not have to reload the game to test the changes he did in the candidate action code.
wesnoth.debug_ai(side)
-- has been added. The function only works in debug mode and returns a table containing the component tree of the active AI for a side, the engine functions and the accessor to the ai.* table of the LuaAI Also allows the user to execute stages and evaluate/execute candidate actions(eval and exec can be run independently).
Structure of the table(example):
{
stage_hello = function: 0x6dc24c0,
ai = #the ai table,
data = {
},
do_moves = function: 0x6dc2590,
candidate_action_evaluation_hello = function: 0x6dc2560,
candidate_action_evaluation_hello2 = function: 0x6dc2640,
components = {
id = "",
stage = {
another_stage = {
name = "another_stage",
id = "",
exec = function: 0x17cd3bb,
engine = "lua",
stg_ptr = "userdata: 0x7c5a8d0"
},
testing_ai_default::candidate_action_evaluation_loop = {
name = "testing_ai_default::candidate_action_evaluation_loop",
candidate_action = {
external = {
name = "external",
id = "",
exec = function: 0x17cd2f3,
engine = "lua",
ca_ptr = "userdata: 0x6fb3600"
},
second = {
name = "second",
id = "",
exec = function: 0x17cd2f3,
engine = "lua",
ca_ptr = "userdata: 0x6fb2f50"
}
},
id = "ca_loop",
exec = function: 0x17cd3bb,
engine = "",
stg_ptr = "userdata: 0x6fb2728"
}
},
engine = "",
name = ""
},
candidate_action_execution_hello2 = function: 0x6dc2670,
candidate_action_execution_hello = function: 0x6dc2530
}
The fields described as " name = function: 0xXXXXXXXX" are functions and can be called to using the usual function call syntax of Lua.
wesnoth.debug_ai(2).ai -- will return the AI table of the Lua AI context.
wesnoth.debug_ai(2).stage[another_stage].exec() -- will execute the stage.
wesnoth.debug_ai(2).ai.get_aggression() -- will the return the current value of the aggression aspect of the AI
Therefore, we have up-to-date access to the whole AI, including the data segment.
NB!: the back-end of this function will be refactored quite drastically and that may involve usage syntax changes. This shouldn't be a big problem, since this function is only used for debugging and won't work in non-debug mode. If something suddenly stops working for you, come back to this page and watch the updates.
See also: Wesnoth AI