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Reflex and Goal-Based Agents - Making Decisions - Coggle Diagram
Reflex and Goal-Based Agents - Making Decisions
Agent Types
Utility-Based Agents: Prefer actions with higher expected utility (value), considering both goals and risks.
Goal-Based Agents: Have a goal they strive to achieve, choosing actions that lead to the goal.
Reflex Agents: Respond directly to the current state of the environment.
Embed in class
User
Simple code
Easy Debugging
Flexible
Intuitive to model
Types
Non-deterministic
In a deterministic environment any action has a single guaranteed effect, and no failure or uncertainty. On the contrary is a non-deterministic environment. In this environment, the same task performed twice may produce different results or may even fail completely
Deterministic
If an agent's current state and selected action can completely determine the next state of the environment, then such environment is called a deterministic environment. A stochastic environment is random in nature and cannot be determined completely by an agent.
FSM (Finite State Machines)
Finite state machine (FSM) is also known as finite state automation. FSM is a calculation model that can be executed with the help of hardware otherwise software.
Application
Logic Controllers: Used in programs, microcontrollers, and circuits.
Game Characters: Ghost behaviour in Pac-Man (chasing, evading, waiting).
Traffic Lights: Cycling through states (red, yellow, green).
. Workshop Challenges & Further Exploration
Workshop Challenge 2: Suggests a coding challenge where participants implement a simple FSM with console output and user-controlled input.
Workshop Challenge 1: Proposes a practical challenge of modeling an enemy with various states, including input factors and state transition table design.
Further Exploration: Provides links to resources for learning more about FSMs, including articles, code examples, and video tutorials.
Model a system
Representation of knowlg
:Agent have make decisions