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Reflex and goal-based agents-making decisions - Coggle Diagram
Reflex and goal-based agents-making decisions
FSM
A finite state machine is a computational framework utilized for creating systems that move between a limited set of states, prompted by events or conditions..
Types of FSM
Deterministic finite state machine (DFSM)
Mealy machine
Non-deterministic finite state machine (NDFSM)
Moore machine
Examples
Traffic light controller (states such as ‘Green,’ ‘Yellow,’ and ‘Red.’)
Elevator control system.(states such as ‘Moving Up,’ ‘Moving Down,’)
Web Links
https://www.spiceworks.com/tech/tech-general/articles/what-is-fsm/
https://www.javatpoint.com/types-of-ai-agents
https://www.geeksforgeeks.org/agents-artificial-intelligence/
Embed in class
Uses
Relatively simple to code
Easy to debug
Intuitive to model
Flexible
Less Processing power
can represent its own history
Types
Deterministic
Non-deterministic
Modeling a System
Representation of Knowledge
System / agents have to make decisions
Agents
Goal-Based
Use searching and planning to decide on actions.
Use goal information to determine actions.
Perform actions to achieve specific goals.
Require knowledge of current state and goals.
Learning Agents
Continuously learn and improve from interactions with the environment.
Useful when multiple alternatives exist.
Start with basic knowledge and adapt over time.
Composed of learning element, critic, performance element, and problem generator.
Model-Based Reflex
Operate in partially observable environments.
Maintain an internal state based on percept history.
Use a model of the world to make decisions.
Track how the world evolves and the effects of their actions.
Simple Reflex
Limited intelligence and adaptability.
Use condition-action rules.
Act based on current percepts, ignoring percept history.
Work best in fully observable environments.