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    Building the AI of F.E.A.R. with Goal Oriented Action Planning | AI 101

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    Building the AI of F.E.A.R. with Goal-Oriented Action Planning | AI 101

    In this episode of AI 101, we will explore goal-oriented action planning, a technique used in the development of the popular video game F.E.A.R. (First Encounter Assault Recon). Goal-oriented action planning (G.O.A.P.) is a method of AI planning that involves creating plans to achieve specific goals in a game. It was popularized by F.E.A.R. and has since been adopted by many other games in the industry.

    Goal-Oriented Action Planning and AI Planning

    Before diving into G.O.A.P., let's first understand the concept of AI planning. AI planning is a process in which a system tries to determine a sequence of actions to achieve a specific goal set by the designer. This is done by modeling the problem in a language or encoding that describes the world's state and the actions that can be taken. These actions have preconditions and effects, which represent the conditions required for an action to be executed and the changes it brings to the world's state.

    In G.O.A.P., the planning process is driven by a finite state machine (FSM) with three states: moving, playing an animation, and using a smart object. These states correspond to different types of actions that the AI character can execute in the game. For example, the AI character can move to a specific location, play an animation to react to the player, or interact with a smart object like opening a door.

    Applying G.O.A.P. in F.E.A.R.

    G.O.A.P. in F.E.A.R. involves assigning goals to AI characters and using a planning system to find a sequence of actions that will help achieve those goals. Each AI character in the game has specific goals, such as patrolling, killing enemies, or avoiding the player. The planner searches through the available actions to find a plan that satisfies the goals of the character.

    The actions in G.O.A.P. are organized in a C++ codebase and are assigned to different AI characters using a separate editor. The game's designers can customize the actions available to each character, making them more versatile in solving their assigned goals. The planner continuously validates the plan during execution, checking if the preconditions and effects of the actions are satisfied. If not, the plan is modified or replanned.


    Goal-oriented action planning, AI planning, F.E.A.R., video game development, finite state machine, G.O.A.P., planning encoding, action space, C++, character goals, action validation, replanning.


    Q: What is goal-oriented action planning (G.O.A.P.)? A: G.O.A.P. is a method of AI planning that involves creating plans to achieve specific goals in a game.

    Q: How is G.O.A.P. applied in video games like F.E.A.R.? A: In games like F.E.A.R., goals are assigned to AI characters, and a planning system is used to find a sequence of actions that help satisfy those goals.

    Q: What are some popular games that use goal-oriented action planning? A: Some popular games that have adopted G.O.A.P. or similar techniques include Condemned: Criminal Origins, STALKER: Shadow of Chernobyl, Deus Ex: Human Revolution, and Middle Earth: Shadow of Mordor.

    Q: What are the benefits of using G.O.A.P. in video game AI? A: G.O.A.P. allows for flexible and dynamic AI behavior by finding plans that satisfy specific goals. It gives AI characters the ability to react and adapt to changing game situations.

    Q: How does G.O.A.P. handle coordination among AI characters? A: G.O.A.P. doesn't inherently handle coordination among AI characters. Cooperative behaviors are created by assigning goals that align with each other, giving the appearance of coordinated behavior.

    Q: Are there any performance concerns with G.O.A.P.? A: The continuous replanning process in G.O.A.P. can create a small performance overhead, especially in complex levels with many AI characters. Optimizations may be needed to ensure smooth gameplay.

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