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Agents and Environments in AI - Coggle Diagram
Agents and Environments in AI
Definition
Autonomous entities capable of perceiving their environment, making decisions, and taking actions to achieve goals.
Types of Agents
Simple Reflex Agents
React based on current percept.
Model-Based Reflex Agents
Maintain an internal state based on the current percept history.
Goal-Based Agents
Maintain goals and take actions to achieve them.
Utility-Based Agents
Evaluate actions based on utility functions.
Utility-Based Agents
Evaluate actions based on utility functions.
Learning Agents
Improve performance over time through learning.
Characteristics
Perception: Ability to sense and interpret the environment.
Action: Ability to perform actions in response to perception.
Autonomy: Ability to operate independently.
Goal-Directed Behavior: Work towards achieving specific objectives.
Communication: Ability to interact with other agents or humans.
Applications
Robotics
Autonomous robots performing tasks in various environments.
Multi-Agent Systems
Coordination between multiple agents to achieve common goals.
Virtual Assistants
AI agents assisting users in tasks like scheduling, searching, and answering questions.
Autonomous Vehicles
Self-driving cars navigating through traffic.
Related Concepts
Environment
The context in which agents operate.
Percept
Sensory input received by the agent.
Action
Response or behavior performed by the agent.
State
Representation of the agent's internal conditions.
Goal
Objective the agent aims to achieve.
Challenges and Future Directions
Scalability: Handling large-scale multi-agent systems.
Coordination: Ensuring effective cooperation between agents.
Adaptability: Adapting to dynamic and uncertain environments.
Ethical Considerations: Ensuring responsible and ethical agent behavior.
Agent = Architecture + Program
An agent's behavior is determined by its architecture and the program it runs.
Task Environment (P.E.A.S.)
Performance Measure: Criterion that defines success.
Environment: External context the agent operates in.
Actuators: Mechanisms through which the agent acts.
Sensors: Mechanisms through which the agent perceives.
Properties of Task Environments
Fully Observable vs. Partially Observable
Single-agent vs. Multi-agent
Deterministic vs. Stochastic
Episodic vs. Sequential
Discrete vs. Continuous
Known vs. Unknown
Web Links
https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_agents_and_environments.htm
https://www.hellotars.com/blog/understanding-ai-agents-and-environments-a-comprehensive-guide/
https://www.javatpoint.com/agent-environment-in-ai
https://www.geeksforgeeks.org/agents-artificial-intelligence/