Introduction-to-Goal-Based-Agents

1. Introduction to Goal-
Based Agents
Goal-based agents are intelligent systems designed to achieve specific
objectives or goals. These agents operate by evaluating their current
state, determining the desired outcome, and selecting the best course of
action to reach that outcome.
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2. Definition and Characteristics of Goal-
Based Agents
1 Autonomy
Goal-based agents have the ability to act independently, making decisions and taking
actions without direct human intervention.
2 Planning and Execution
These agents are capable of formulating plans to achieve their goals and executing those
plans efficiently.
3 Reactivity
They can respond to changes in their environment and modify their actions to adapt to
new situations.

3. Examples of Goal-Based Agents in
Real-World Applications
Autonomous Vehicles
Self-driving cars use goal-based decision-making to navigate and reach their
destinations safely.
Manufacturing Robots
Robotic arms in manufacturing plants are programmed as goal-based agents
to perform precise and repetitive tasks.
Chatbots
Virtual assistants utilize goal-based methods to understand user queries and
provide relevant responses.

4. Advantages and Limitations of Goal-
Based Agents
Advantages
Goal-based agents are efficient in achieving
specific tasks, adaptable to changing scenarios,
and can handle complex decision-making
processes.
Limitations
They may struggle in uncertain or dynamic
environments and require well-defined goals to
operate effectively.

5. Introduction to Utility-Based Agents
Utility-based agents are intelligent systems that make decisions based on maximizing the expected utility
or value of their actions. These agents evaluate different actions in terms of their desirability and select
the one that provides the highest utility.

6. Definition and Characteristics of Utility-
Based Agents
1 Utility Function
Utility-based agents use a utility function to assign values to possible outcomes, allowing
them to make rational decisions.
2 Decision Theory
They operate within the framework of decision theory, analyzing actions in terms of their
potential outcomes and associated utilities.
3 Risk Assessment
These agents can factor in risk and uncertainty when evaluating the desirability of
different actions.

7. Examples of Utility-Based Agents in
Real-World Applications
Financial Investment Systems
Utility-based agents are used to evaluate potential investments and optimize portfolios
based on risk and return preferences.
Medical Diagnosis Systems
Diagnostic tools utilize utility-based decision-making to evaluate symptoms and
recommend the most effective treatment options.
Smart Home Automation
Home automation systems make use of utility-based methods to optimize energy usage
and enhance user comfort.

8. Advantages and Limitations of Utility-
Based Agents
Advantages
Utility-based agents can handle complex
decision-making under uncertainty, allowing for
rational and optimized solutions.
Limitations
They rely heavily on accurate utility estimations
and may encounter challenges in scenarios with
significant unknown variables.