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Adaptive and objective-driven agents - formulating choices - Coggle Diagram
Adaptive and objective-driven agents - formulating choices
Introduction:
An artificial intelligence agent is made to act in response to its surroundings. The agent uses predefined rules to decide how to react when an event happens in its environment by consulting its knowledge base.
Types
• Simple reflex
• Model-based reflex
• Goal-based
• Utility-based
Limited State Mach
• This method is useful for effectively managing a variety of states.
• Both fresh perceptual inputs and prior states have an impact on current states.
Every state establishes norms for conduct and sets in motion.
• States change depending on regulations and circumstances.
• Transitions between states are governed by regulations and requirements.
• State transitions are triggered by input events.
Modeling a system involves:
• Representation of knowledge.
• Agents making decisions based on this representation.
Uses
Uses of this approach include:
• Relatively simple coding process.
• Easy debugging due to its straightforward nature.
• Requires less processing power as it follows hard-coded rules (resulting in lower intelligence).
• Intuitive to model.
• Flexible, allowing for behavior adjustments.
• Capable of representing its own history.