MistreevousSharp

MistreevousSharp is a lightweight, C# behaviour tree library for .NET 9.0 and .NET Standard 2.1, ported from the original mistreevous TypeScript library. Define complex AI behaviours using either JSON or a clean, minimal DSL (MDSL). Built for modularity, clarity, and fast iteration — perfect for games, simulations, and interactive agents.

✨ Key Features

🔹 Minimal DSL or JSON-based definitions – define behaviours clearly and concisely
🔹 Built-in composite, decorator & leaf nodes – model complex logic using a toolbox of predefined node types
🔹 Async & promise-based actions – handle long-running behaviours and actions asynchronously
🔹 Lifecycle callbacks – define callbacks to invoke when tree nodes start, resume, or finish processing
🔹 Global functions & subtrees – reuse logic and subtree definitions across multiple agents
🔹 Guards – dynamically interrupt or cancel long-running behaviours
🔹 Randomised behaviour – weighted choices, random delays, seedable RNG for deterministic tree processing
🔹 Debugging tools – inspect the state of running tree instances and track node state changes
🔹 Optimized for performance – reduced memory allocations, perfect for Unity, Godot, or game servers
🔹 Cross-platform – works on .NET 9.0, .NET Standard 2.1, Unity, and more

🌳 What are Behaviour Trees?
Behaviour trees are hierarchical structures designed to model decision-making processes and are used to create complex AI via the modular composition of individual tasks, making it easy to sequence actions, handle conditions, and control flow in a readable and maintainable way.

🛠️ There is an in-browser editor and tree visualiser for the original TypeScript library that you can try HERE (MDSL definitions are compatible!)

Install

NuGet Package Manager

Install-Package MistreevousSharp

.NET CLI

dotnet add package MistreevousSharp

PackageReference

<PackageReference Include="MistreevousSharp" Version="1.0.0" />

Example

using Mistreevous;

// Define some behaviour for an agent.
var definition = @"root {
    sequence {
        action [Walk]
        action [Fall]
        action [Laugh]
    }
}";

// Create an agent that we will be modelling the behaviour for.
var agent = new MyAgent();

// Create the behaviour tree, passing our tree definition and the agent.
var behaviourTree = new BehaviourTree(definition, agent);

// Step the tree.
behaviourTree.Step();

// Output:
// 'walking!'
// 'falling!'
// 'laughing!'

Agent Implementation

public class MyAgent : IAgent
{
    public object? this[string propertyName] => 
        GetType().GetProperty(propertyName)?.GetValue(this);

    public State Walk()
    {
        Console.WriteLine("walking!");
        return State.Succeeded;
    }

    public State Fall()
    {
        Console.WriteLine("falling!");
        return State.Succeeded;
    }

    public State Laugh()
    {
        Console.WriteLine("laughing!");
        return State.Succeeded;
    }
}

Behaviour Tree Methods

IsRunning()

Returns true if the tree is in the RUNNING state, otherwise false.

GetState()

Gets the current tree state of SUCCEEDED, FAILED, READY or RUNNING.

Step()

Carries out a node update that traverses the tree from the root node outwards to any child nodes, skipping those that are already in a resolved state of SUCCEEDED or FAILED. After being updated, leaf nodes will have a state of SUCCEEDED, FAILED or RUNNING. Leaf nodes that are left in the RUNNING state as part of a tree step will be revisited each subsequent step until they move into a resolved state of either SUCCEEDED or FAILED, after which execution will move through the tree to the next node with a state of READY.

Calling this method when the tree is already in a resolved state of SUCCEEDED or FAILED will cause it to be reset before tree traversal begins.

Reset()

Resets the tree from the root node outwards to each nested node, giving each a state of READY.

GetTreeNodeDetails()

Gets the details of every node in the tree, starting from the root. This will include the current state of each node, which is useful for debugging a running tree instance.

Behaviour Tree Options

The BehaviourTree constructor can take an options object as an argument, the properties of which are shown below.

Option	Type	Description
GetDeltaTime	`Func<double>`	A function returning a delta time in seconds that is used to calculate the elapsed duration of any `wait` nodes. If this function is not defined then `DateTime.UtcNow` is used instead by default.
Random	`Func<double>`	A function returning a floating-point number between 0 (inclusive) and 1 (exclusive). If defined, this function is used to source a pseudo-random number to use in operations such as the selection of active children for any `lotto` nodes as well as the selection of durations for `wait` nodes, iterations for `repeat` nodes and attempts for `retry` nodes when minimum and maximum bounds are defined. If not defined then `Random.NextDouble()` will be used instead by default. This function can be useful in seeding all random numbers used in the running of a tree instance to make any behaviour completely deterministic.
OnNodeStateChange	`Action<NodeStateChange>`	An event handler that is called whenever the state of a node changes. The change object will contain details of the updated node and will include the previous state and current state.

Nodes

States

Behaviour tree nodes can be in one of the following states:

READY A node is in the READY state when it has not been visited yet in the execution of the tree.
RUNNING A node is in the RUNNING state when it is still being processed, these nodes will usually represent or encompass a long-running action.
SUCCEEDED A node is in a SUCCEEDED state when it is no longer being processed and has succeeded.
FAILED A node is in the FAILED state when it is no longer being processed but has failed.

Composite Nodes

Composite nodes wrap one or more child nodes, each of which will be processed in a sequence determined by the type of the composite node. A composite node will remain in the RUNNING state until it is finished processing the child nodes, after which the state of the composite node will reflect the success or failure of the child nodes.

Sequence

This composite node will update each child node in sequence. It will move to the SUCCEEDED state if all of its children have moved to the SUCCEEDED state and will move to the FAILED state if any of its children move to the FAILED state. This node will remain in the RUNNING state if one of its children remains in the RUNNING state.

MDSL

root {
    sequence {
        action [Walk]
        action [Fall]
        action [Laugh]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "children": [
            {
                "type": "action",
                "call": "Walk"
            },
            {
                "type": "action",
                "call": "Fall"
            },
            {
                "type": "action",
                "call": "Laugh"
            }
        ]
    }
}

Selector

This composite node will update each child node in sequence. It will move to the FAILED state if all of its children have moved to the FAILED state and will move to the SUCCEEDED state if any of its children move to the SUCCEEDED state. This node will remain in the RUNNING state if one of its children is in the RUNNING state.

MDSL

root {
    selector {
        action [TryThis]
        action [ThenTryThis]
        action [TryThisLast]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "selector",
        "children": [
            {
                "type": "action",
                "call": "TryThis"
            },
            {
                "type": "action",
                "call": "ThenTryThis"
            },
            {
                "type": "action",
                "call": "TryThisLast"
            }
        ]
    }
}

Parallel

This composite node will update each child node concurrently. It will move to the SUCCEEDED state if all of its children have moved to the SUCCEEDED state and will move to the FAILED state if any of its children move to the FAILED state, otherwise it will remain in the RUNNING state.

MDSL

root {
    parallel {
        action [RubBelly]
        action [PatHead]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "parallel",
        "children": [
            {
                "type": "action",
                "call": "RubBelly"
            },
            {
                "type": "action",
                "call": "PatHead"
            }
        ]
    }
}

Race

This composite node will update each child node concurrently. It will move to the SUCCEEDED state if any of its children have moved to the SUCCEEDED state and will move to the FAILED state if all of its children move to the FAILED state, otherwise it will remain in the RUNNING state.

MDSL

root {
    race {
        action [UnlockDoor]
        action [FindAlternativePath]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "race",
        "children": [
            {
                "type": "action",
                "call": "UnlockDoor"
            },
            {
                "type": "action",
                "call": "FindAlternativePath"
            }
        ]
    }
}

All

This composite node will update each child node concurrently. It will stay in the RUNNING state until all of its children have moved to either the SUCCEEDED or FAILED state, after which this node will move to the SUCCEEDED state if any of its children have moved to the SUCCEEDED state, otherwise it will move to the FAILED state.

MDSL

root {
    all {
        action [Reload]
        action [MoveToCover]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "all",
        "children": [
            {
                "type": "action",
                "call": "Reload"
            },
            {
                "type": "action",
                "call": "MoveToCover"
            }
        ]
    }
}

Lotto

This composite node will select a single child at random to run as the active running node. The state of this node will reflect the state of the active child.

MDSL

root {
    lotto {
        action [MoveLeft]
        action [MoveRight]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "lotto",
        "children": [
            {
                "type": "action",
                "call": "MoveLeft"
            },
            {
                "type": "action",
                "call": "MoveRight"
            }
        ]
    }
}

A probability weight can be defined for each child node as an optional integer node argument in MDSL, influencing the likelihood that a particular child will be picked. In JSON this would be done by setting a value of an array containing the integer weight values for the weights property.

MDSL

root {
    lotto [10,5,3,1] {
        action [CommonAction]
        action [UncommonAction]
        action [RareAction]
        action [VeryRareAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "lotto",
        "children": [
            {
                "type": "action",
                "call": "CommonAction"
            },
            {
                "type": "action",
                "call": "UncommonAction"
            },
            {
                "type": "action",
                "call": "RareAction"
            },
            {
                "type": "action",
                "call": "VeryRareAction"
            }
        ],
        "weights": [10, 5, 3, 1]
    }
}

Decorator Nodes

A decorator node is similar to a composite node, but it can only have a single child node. The state of a decorator node is usually some transformation of the state of the child node. Decorator nodes are also used to repeat or terminate the execution of a particular node.

Root

This decorator node represents the root of a behaviour tree and cannot be the child of another composite node.

The state of a root node will reflect the state of its child node.

MDSL

root {
    action [Dance]
}

JSON

{
    "type": "root",
    "child": {
        "type": "action",
        "call": "Dance"
    }
}

Additional named root nodes can be defined and reused throughout a definition. Other root nodes can be referenced via the branch node. Exactly one root node must be left unnamed, this root node will be used as the main root node for the entire tree.

MDSL

root {
    branch [SomeOtherTree]
}

root [SomeOtherTree] {
    action [Dance]
}

JSON

[
    {
        "type": "root",
        "child": {
            "type": "branch",
            "ref": "SomeOtherTree"
        }
    },
    {
        "type": "root",
        "id": "SomeOtherTree",
        "child": {
            "type": "action",
            "call": "Dance"
        }
    }
]

Repeat

This decorator node will repeat the execution of its child node if the child moves to the SUCCEEDED state. It will do this until either the child moves to the FAILED state, at which point the repeat node will move to the FAILED state, or the maximum number of iterations is reached, which moves the repeat node to the SUCCEEDED state. This node will be in the RUNNING state if its child is also in the RUNNING state, or if further iterations need to be made.

The maximum number of iterations can be defined as a single integer iteration argument in MDSL, or by setting the iterations property in JSON. In the example below, we would be repeating the action SomeAction 5 times.

MDSL

root {
    repeat [5] {
        action [SomeAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "repeat",
        "iterations": 5,
        "child": {
            "type": "action",
            "call": "SomeAction"
        }
    }
}

The number of iterations to make can be selected at random within a lower and upper bound if these are defined as two integer arguments in MDSL, or by setting a value of an array containing two integer values for the iterations property in JSON. In the example below, we would be repeating the action SomeAction between 1 and 5 times.

MDSL

root {
    repeat [1,5] {
        action [SomeAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "repeat",
        "iterations": [1, 5],
        "child": {
            "type": "action",
            "call": "SomeAction"
        }
    }
}

The maximum number of iterations to make can be omitted. This would result in the child node being run infinitely, as can be seen in the example below.

MDSL

root {
    repeat {
        action [SomeAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "repeat",
        "child": {
            "type": "action",
            "call": "SomeAction"
        }
    }
}

Retry

This decorator node will repeat the execution of its child node if the child moves to the FAILED state. It will do this until either the child moves to the SUCCEEDED state, at which point the retry node will move to the SUCCEEDED state or the maximum number of attempts is reached, which moves the retry node to the FAILED state. This node will be in a RUNNING state if its child is also in the RUNNING state, or if further attempts need to be made.

The maximum number of attempts can be defined as a single integer attempt argument in MDSL, or by setting the attempts property in JSON. In the example below, we would be retrying the action SomeAction 5 times.

MDSL

root {
    retry [5] {
        action [SomeAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "retry",
        "attempts": 5,
        "child": {
            "type": "action",
            "call": "SomeAction"
        }
    }
}

The number of attempts to make can be selected at random within a lower and upper bound if these are defined as two integer arguments in MDSL, or by setting a value of an array containing two integer values for the attempts property in JSON. In the example below, we would be retrying the action SomeAction between 1 and 5 times.

MDSL

root {
    retry [1,5] {
        action [SomeAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "retry",
        "attempts": [1, 5],
        "child": {
            "type": "action",
            "call": "SomeAction"
        }
    }
}

The maximum number of attempts to make can be omitted. This would result in the child node being run infinitely until it moves to the SUCCEEDED state, as can be seen in the example below.

MDSL

root {
    retry {
        action [SomeAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "retry",
        "child": {
            "type": "action",
            "call": "SomeAction"
        }
    }
}

Flip

This decorator node will move to the SUCCEEDED state when its child moves to the FAILED state, and it will move to the FAILED if its child moves to the SUCCEEDED state. This node will remain in the RUNNING state if its child is in the RUNNING state.

MDSL

root {
    flip {
        action [SomeAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "flip",
        "child": {
            "type": "action",
            "call": "SomeAction"
        }
    }
}

Succeed

This decorator node will move to the SUCCEEDED state when its child moves to either the FAILED state or the SUCCEEDED state. This node will remain in the RUNNING state if its child is in the RUNNING state.

MDSL

root {
    succeed {
        action [SomeAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "succeed",
        "child": {
            "type": "action",
            "call": "SomeAction"
        }
    }
}

Fail

This decorator node will move to the FAILED state when its child moves to either the FAILED state or the SUCCEEDED state. This node will remain in the RUNNING state if its child is in the RUNNING state.

MDSL

root {
    fail {
        action [SomeAction]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "fail",
        "child": {
            "type": "action",
            "call": "SomeAction"
        }
    }
}

Leaf Nodes

Leaf nodes are the lowest-level node type and cannot be the parent of other child nodes.

Action

An action node represents an action that can be completed immediately as part of a single tree step, or ongoing behaviour that can take a prolonged amount of time and may take multiple tree steps to complete. Each action node will correspond to some action that can be carried out by the agent, where the first action node argument (if using MDSL, or the call property if using JSON) will be an identifier matching the name of the corresponding agent action function or globally registered function.

An agent action function can optionally return a value of State.Succeeded, State.Failed or State.Running. If the State.Succeeded or State.Failed state is returned, then the action will move to that state.

MDSL

root {
    action [Attack]
}

JSON

{
    "type": "root",
    "child": {
        "type": "action",
        "call": "Attack"
    }
}

public class MyAgent : IAgent
{
    public object? this[string propertyName] => 
        GetType().GetProperty(propertyName)?.GetValue(this);

    public State Attack()
    {
        // If we do not have a weapon then we cannot attack.
        if (!IsHoldingWeapon())
        {
            // We have failed to carry out an attack!
            return State.Failed;
        }

        // ... Attack with swiftness and precision ...

        // We have carried out our attack.
        return State.Succeeded;
    }
}

If no value or a value of State.Running is returned from the action function the action node will move into the RUNNING state and no following nodes will be processed as part of the current tree step. In the example below, any action node that references WalkToPosition will remain in the RUNNING state until the target position is reached.

public State WalkToPosition()
{
    // ... Walk towards the position we are trying to reach ...

    // Check whether we have finally reached the target position.
    if (IsAtTargetPosition())
    {
        // We have finally reached the target position!
        return State.Succeeded;
    }

    // We have not reached the target position yet.
    return State.Running;
}

Further steps of the tree will resume processing from leaf nodes that were left in the RUNNING state until those nodes move to either the SUCCEEDED or FAILED state or processing of the running branch is aborted via a guard.

Async Actions

As well as returning a finished action state from an action function, you can also return a Task<State> that should eventually resolve with a finished state of State.Succeeded or State.Failed as its value. The action will remain in the RUNNING state until the task is fulfilled, and any following tree steps will not call the action function again.

public async Task<State> SomeAsyncAction()
{
    await Task.Delay(5000);
    return State.Succeeded;
}

Optional Arguments

Arguments can optionally be passed to agent action functions. In MDSL these optional arguments must be defined after the action name identifier argument and can be a number, string, boolean, null or agent property reference. If using JSON then these arguments are defined in an args array and these arguments can be any valid JSON.

MDSL

root {
    action [Say, "hello world", 5, true]
}

JSON

{
    "type": "root",
    "child": {
        "type": "action",
        "call": "Say",
        "args": ["hello world", 5, true]
    }
}

public State Say(string dialog, int times = 1, bool sayLoudly = false)
{
    for (int index = 0; index < times; index++)
    {
        ShowDialog(sayLoudly ? dialog.ToUpper() + "!!!" : dialog);
    }

    return State.Succeeded;
}

Condition

A Condition node will immediately move into either a SUCCEEDED or FAILED state based on the boolean result of calling either an agent function or globally registered function. The first condition node argument will be an identifier matching the name of the corresponding agent condition function or globally registered function (if using MDSL, or the call property if using JSON).

MDSL

root {
    sequence {
        condition [HasWeapon]
        action [Attack]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "children": [
            {
                "type": "condition",
                "call": "HasWeapon"
            },
            {
                "type": "action",
                "call": "Attack"
            }
        ]
    }
}

public class MyAgent : IAgent
{
    public object? this[string propertyName] => 
        GetType().GetProperty(propertyName)?.GetValue(this);

    public bool HasWeapon() => IsHoldingWeapon();
    public State Attack() => AttackPlayer();
}

Optional Arguments

Arguments can optionally be passed to agent condition functions in the same way as action nodes. In MDSL these optional arguments must be defined after the condition name identifier argument, and can be a number, string, boolean, null or agent property reference.

MDSL

root {
    sequence {
        condition [HasItem, "potion"]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "children": [
            {
                "type": "condition",
                "call": "HasItem",
                "args": ["potion"]
            }
        ]
    }
}

public bool HasItem(string itemName) => Inventory.Contains(itemName);

Wait

A wait node will remain in a RUNNING state for a specified duration, after which it will move into the SUCCEEDED state. The duration in milliseconds can be defined as an optional single integer node argument in MDSL, or by setting a value for the duration property in JSON.

MDSL

root {
    repeat {
        sequence {
            action [FireWeapon]
            wait [2000]
        }
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "repeat",
        "child": {
            "type": "sequence",
            "children": [
                {
                    "type": "action",
                    "call": "FireWeapon"
                },
                {
                    "type": "wait",
                    "duration": 2000
                }
            ]
        }
    }
}

In the above example, we are using a wait node to wait 2 seconds between each run of the FireWeapon action.

The duration to wait in milliseconds can also be selected at random within a lower and upper bound if these are defined as two integer node arguments in MDSL, or by setting a value of an array containing two integer values for the duration property in JSON. In the example below, we would run the PickUpProjectile action and then wait for 2 to 8 seconds before running the ThrowProjectile action.

MDSL

root {
    sequence {
        action [PickUpProjectile]
        wait [2000, 8000]
        action [ThrowProjectile]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "children": [
            {
                "type": "action",
                "call": "PickUpProjectile"
            },
            {
                "type": "wait",
                "duration": [2000, 8000]
            },
            {
                "type": "action",
                "call": "ThrowProjectile"
            }
        ]
    }
}

If no duration is defined then the wait node will remain in the RUNNING state indefinitely until it is aborted.

MDSL

root {
    wait
}

JSON

{
    "type": "root",
    "child": {
        "type": "wait"
    }
}

Branch

Named root nodes can be referenced using the branch node. This node acts as a placeholder that will be replaced by the child node of the referenced root node. All definitions below are synonymous.

MDSL

root {
    branch [SomeOtherTree]
}

root [SomeOtherTree] {
    action [Dance]
}

root {
    action [Dance]
}

JSON

[
    {
        "type": "root",
        "child": {
            "type": "branch",
            "ref": "SomeOtherTree"
        }
    },
    {
        "type": "root",
        "id": "SomeOtherTree",
        "child": {
            "type": "action",
            "call": "Dance"
        }
    }
]

{
    "type": "root",
    "child": {
        "type": "action",
        "call": "Dance"
    }
}

Callbacks

Callbacks can be defined for tree nodes and will be invoked as the node is processed during a tree step. Any number of callbacks can be attached to a node as long as there are not multiple callbacks of the same type.

Callbacks are perfect for triggering animations, effects, sounds, logging, or side effects without bloating your action functions.

Optional arguments can be defined for callback functions in the same way as action and condition functions.

Entry

An entry callback defines an agent function or globally registered function to call whenever the associated node moves into the RUNNING state when it is first visited.

MDSL

root {
    sequence entry(StartWalkingAnimation)  {
        action [WalkNorthOneSpace]
        action [WalkEastOneSpace]
        action [WalkSouthOneSpace]
        action [WalkWestOneSpace]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "entry": {
            "call": "StartWalkingAnimation"
        },
        "children": [
            {
                "type": "action",
                "call": "WalkNorthOneSpace"
            },
            {
                "type": "action",
                "call": "WalkEastOneSpace"
            },
            {
                "type": "action",
                "call": "WalkSouthOneSpace"
            },
            {
                "type": "action",
                "call": "WalkWestOneSpace"
            }
        ]
    }
}

Exit

An exit callback defines an agent function or globally registered function to call whenever the associated node moves to a state of SUCCEEDED or FAILED or is aborted. A results object is passed to the referenced function containing the succeeded and aborted boolean properties.

MDSL

root {
    sequence entry(StartWalkingAnimation) exit(StopWalkingAnimation) {
        action [WalkNorthOneSpace]
        action [WalkEastOneSpace]
        action [WalkSouthOneSpace]
        action [WalkWestOneSpace]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "entry": {
            "call": "StartWalkingAnimation"
        },
        "exit": {
            "call": "StopWalkingAnimation"
        },
        "children": [
            {
                "type": "action",
                "call": "WalkNorthOneSpace"
            },
            {
                "type": "action",
                "call": "WalkEastOneSpace"
            },
            {
                "type": "action",
                "call": "WalkSouthOneSpace"
            },
            {
                "type": "action",
                "call": "WalkWestOneSpace"
            }
        ]
    }
}

Step

A step callback defines an agent function or globally registered function to call whenever the associated node is updated as part of a tree step.

MDSL

root {
    sequence step(OnMoving) {
        action [WalkNorthOneSpace]
        action [WalkEastOneSpace]
        action [WalkSouthOneSpace]
        action [WalkWestOneSpace]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "step": {
            "call": "OnMoving"
        },
        "children": [
            {
                "type": "action",
                "call": "WalkNorthOneSpace"
            },
            {
                "type": "action",
                "call": "WalkEastOneSpace"
            },
            {
                "type": "action",
                "call": "WalkSouthOneSpace"
            },
            {
                "type": "action",
                "call": "WalkWestOneSpace"
            }
        ]
    }
}

Optional Arguments

Arguments can optionally be passed to agent callback functions and can be a number, string, boolean, null or agent property reference.

MDSL

root {
    action [Walk] entry(OnMovementStart, "walking")
}

JSON

{
    "type": "root",
    "child": {
        "type": "action",
        "call": "Walk",
        "entry": {
            "call": "OnMovementStart",
            "args": [
                "walking"
            ]
        }
    }
}

Guards

A guard defines a condition that must be met in order for the associated node to remain active. Any nodes in the RUNNING state will have their guard condition evaluated for each leaf node update and will move to the FAILED state by default if the guard condition is not met.

This functionality is useful as a means of aborting long-running actions or branches that span across multiple steps of the tree.

MDSL

root {
    wait while(CanWait)
}

JSON

{
    "type": "root",
    "child": {
        "type": "wait",
        "while": {
            "call": "CanWait"
        }
    }
}

In the above example, we have a wait node that waits indefinitely. We are using a while guard to give up on waiting if the guard function CanWait returns false during a tree step.

Optional Arguments

Arguments can optionally be passed to agent guard functions and can be a number, string, boolean, null or agent property reference.

MDSL

root {
    action [Run] while(HasItemEquipped, "running-shoes")
}

root {
    action [Gamble] until(HasGold, 1000)
}

JSON

{
    "type": "root",
    "child": {
        "type": "action",
        "call": "Run",
        "while": {
            "call": "HasItemEquipped",
            "args": [
                "running-shoes"
            ]
        }
    }
}

{
    "type": "root",
    "child": {
        "type": "action",
        "call": "Gamble",
        "until": {
            "call": "HasGold",
            "args": [
                1000
            ]
        }
    }
}

While

A while guard will be satisfied as long as its condition evaluates to true.

MDSL

root {
    sequence while(IsWandering) {
        action [Whistle]
        wait [5000]
        action [Yawn]
        wait [5000]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "while": {
            "call": "IsWandering"
        },
        "children": [
            {
                "type": "action",
                "call": "Whistle"
            },
            {
                "type": "wait",
                "duration": 5000
            },
            {
                "type": "action",
                "call": "Yawn"
            },
            {
                "type": "wait",
                "duration": 5000
            }
        ]
    }
}

Until

An until guard will be satisfied as long as its condition evaluates to false.

MDSL

root {
    sequence until(CanSeePlayer) {
        action [LookLeft]
        wait [5000]
        action [LookRight]
        wait [5000]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "until": {
            "call": "CanSeePlayer"
        },
        "children": [
            {
                "type": "action",
                "call": "LookLeft"
            },
            {
                "type": "wait",
                "duration": 5000
            },
            {
                "type": "action",
                "call": "LookRight"
            },
            {
                "type": "wait",
                "duration": 5000
            }
        ]
    }
}

Defining Aborted Node State

When aborted via a guard, a node will move to the FAILED state by default. Optionally, the state that the node should move to when aborted can be specified with then succeed or then fail following the guard definition when using MDSL, or by setting the succeedOnAbort boolean property when using a JSON definition.

MDSL

root {
    sequence {
        wait until(CanAttack) then succeed
        action [Attack]
    }
}

JSON

{
    "type": "root",
    "child": {
        "type": "sequence",
        "children": [
            {
                "type": "wait",
                "until": {
                    "call": "CanAttack",
                    "succeedOnAbort": true
                }
            },
            {
                "type": "action",
                "call": "Attack"
            }
        ]
    }
}

Referencing Agent Properties as Arguments

In addition to passing literal values (number, string, boolean, or null) as arguments to agent functions, agent properties can also be referenced dynamically in both MDSL and JSON definitions.

This allows argument values to be resolved from the agent instance at runtime, enabling more flexible and data-driven behaviour definitions. Any referenced property must exist on the agent instance, either as a field or a getter method.

In MDSL, agent properties are referenced by adding a $ prefix to the argument. The portion following the $ is interpreted as the name of a property on the agent, and its current value will be passed to the agent function when invoked.

In JSON definitions, agent property references are represented as object literals with a single property where the key is $ and where the value is the name of the agent property to resolve.

In these examples, the value of agent.SomeAgentProperty is passed as the argument to SomeFunction.

MDSL

root {
    action [SomeFunction, $someAgentProperty]
}

JSON

{
    "type": "root",
    "child": {
        "type": "action",
        "call": "SomeFunction",
        "args": [
            { "$": "someAgentProperty" }
        ]
    }
}

Globals

When dealing with multiple agents, each with its own behaviour tree instance, it can often be useful to have functions and subtrees that can be registered globally once and referenced by any instance.

Global Subtrees

We can globally register a subtree that can be referenced from any behaviour tree via a branch node.

// Register the global subtree for some celebratory behaviour. We can also pass a JSON definition here.
BehaviourTree.Register("Celebrate", @"root {
    sequence {
        action [Jump]
        action [Say, ""Yay!""]
        action [Jump]
        action [Say, ""We did it!""]
    }
}");

// Define some behaviour for an agent that references our registered 'Celebrate' subtree.
var definition = @"root {
    sequence {
        action [AttemptDifficultTask]
        branch [Celebrate]
    }
}";

// Create our agent behaviour tree.
var agentBehaviourTree = new BehaviourTree(definition, agent);

Global Functions

We can globally register functions to be invoked in place of any agent instance functions, these functions can be referenced throughout a tree definition anywhere that we can reference an agent instance function. The primary difference between these globally registered functions and any agent instance functions is that all global functions that are invoked will take the invoking agent object as the first argument, followed by any optional arguments.

In a situation where a tree will reference a function by name that is defined on both the agent instance as well as a function that is registered globally, the agent instance function will take precedence.

// Register the 'speak' global function that any agent tree can invoke for an action.
GlobalFunction speakFunction = (IAgent agent, params object?[] args) =>
{
    var text = args[0]?.ToString() ?? "";
    ShowInfoToast($"{agent.GetType().Name}: {text}");
    return State.Succeeded;
};
BehaviourTree.Register("Speak", speakFunction);

// Register the 'IsSimulationRunning' global function that any agent tree can invoke for a condition.
GlobalFunction isSimulationRunningFunction = (IAgent agent, params object?[] args) =>
{
    return Simulation.IsRunning();
};
BehaviourTree.Register("IsSimulationRunning", isSimulationRunningFunction);

// Define some behaviour for an agent that references our registered functions.
var definition = @"root {
    sequence {
        condition [IsSimulationRunning]
        action [Speak, ""I still have work to do""]
    }
}";

// Create our agent behaviour tree.
var agentBehaviourTree = new BehaviourTree(definition, agent);

Performance

This library has been optimized to reduce memory allocations and improve performance, especially important for use in game engines and real-time systems. Key optimizations include:

Manual array/list operations to avoid LINQ allocations
Thread-local storage for reusable collections
Efficient node state management
Minimal object creation during tree traversal

See the GitHub Wiki for details on the optimizations applied.

Compatibility

This library maintains compatibility with:

MDSL definitions from the original TypeScript library
JSON definitions from the original TypeScript library
API similar to the original TypeScript library

You can use the in-browser visualiser to design your trees and then use them directly in your C# projects!

Documentation

For detailed documentation, please visit the GitHub Wiki:

License

MIT (same license as the original library)

Credits

This library is a C# port of the excellent mistreevous TypeScript library by nikkorn. All credit for the original design and implementation goes to the original author.

Name		Name	Last commit message	Last commit date
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.github/workflows		.github/workflows
.idea/.idea.MistreevousSharp/.idea		.idea/.idea.MistreevousSharp/.idea
assets		assets
example		example
src/Mistreevous		src/Mistreevous
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
MistreevousSharp.sln		MistreevousSharp.sln
README.md		README.md

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MistreevousSharp

✨ Key Features

Install

NuGet Package Manager

.NET CLI

PackageReference

Example

Agent Implementation

Behaviour Tree Methods

IsRunning()

GetState()

Step()

Reset()

GetTreeNodeDetails()

Behaviour Tree Options

Nodes

States

Composite Nodes

Sequence

Selector

Parallel

Race

All

Lotto

Decorator Nodes

Root

Repeat

Retry

Flip

Succeed

Fail

Leaf Nodes

Action

Async Actions

Optional Arguments

Condition

Optional Arguments

Wait

Branch

Callbacks

Entry

Exit

Step

Optional Arguments

Guards

Optional Arguments

While

Until

Defining Aborted Node State

Referencing Agent Properties as Arguments

Globals

Global Subtrees

Global Functions

Performance

Compatibility

Documentation

Further Reading

License

Credits

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