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Reflex and goal-based agents - Coggle Diagram
Reflex and goal-based agents
Introduction
Reflex agents are a type of intelligent agent that make decisions based on the current percept, ignoring the rest of the percept history. They operate by using a set of condition-action rules, or reflexes, to respond to changes in the environment.
Types of Agents
Simple Reflex
Model-based Reflex
Goal-based
Utility-based
Finite State Machine (FSM)
Concept:
States are defined by previous states and inputs.
Transitions occur based on rules and conditions.
Example: Ghost behavior in Pac-Man:
States: Waiting at home, chasing, evading.
Transitions: Based on Pac-Man's actions (e.g., power-up).
Modelling a System
Decision Making: Process of selecting actions based on the agent's knowledge and goals.
Knowledge Representation: How the agent represents knowledge about the world.
State Design Pattern
Logic Embedded in State Class: Each state is a class with methods to handle transitions.
Example Diagram for Miner Bob: Illustrates states and transitions for a character.
Advantages:
Simple to code and debug.
Less processing power required.
Intuitive and flexible modeling.
Web-Site
https://www.javatpoint.com/types-of-ai-agents
https://arxiv.org/abs/2009.05161
https://www.baeldung.com/cs/goal-based-vs-utility-based-agents