Lecture_11_-_Decision_Trees_-_State_Machines_ppt

Decision Tree

A series of questions that help a unit decide what to do given its current situation, often structured as yes/no questions leading to different states.

Finite State Machine (FSM)

A computational model that can be in one of a finite number of states at any given time and changes states based on input conditions.

Hierarchical State Machines

State machines where states can have substates, allowing for a more organized and manageable structure.

Action Request

A request for an action to be performed by a character or system based on internal or external knowledge changes.

Binary Decision Tree

A type of decision tree where each decision leads to one of two branches, creating a binary structure.

C++ Style in Decision Trees

Implementation of decision trees using C++ syntax to create node structures and manage decision logic.

Pros of FSM

Easy to write and fast to implement, suitable for smaller state machines.

Cons of FSM

Can become difficult to maintain, particularly as state machines grow in complexity.

Random Decision Trees

Decision trees that incorporate randomness in decision making, often used for unpredictable AI behavior.

FSM Scripting Language

A scripting language used by designers to modify behavior without the need for compilation after changes.

Action

A specific behavior that a character may perform in response to certain conditions being met.

Pros of Macros in FSM

Provide structure and consistent formatting across all state machines, aiding readability and debugging.

Cons of Macros in FSM

Hard to maintain when adding macros, requiring careful planning of requirements.

State Transition

The movement from one state to another based on specific conditions being met.

Object-Oriented FSM

A finite state machine structured around object-oriented programming concepts to manage states and transitions.