Copy of 2.GOAL Based Agent edited PDF

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Goal based agent details,how it works with example.Explained in a very easy way so that everyone could understand easily....

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GOAL – BASED AGENT What is a Goal Based agent? : Expansion of model based reflex agent. It has a model based basic purpose and has knowledge of the past. extra is, it knows what should be the output. It k nows what the goal state looks like. searching and planning is its main purpose. A goal-based agent has flexibility to adjust its actions based on successfully reaching a goal. In this lesson, you'll learn more about this agent in artificial intelligence and how it differs from a model-based agent.  ? Think about implementation without hardware ? Benefit of GBA

Action choosing : Achieving the goals can take 1 action or many actions. Search and planning are two subfields in AI devoted to finding sequences of actions to achieve an agent’s goals. Unlike the previous reflex agents before acting this agent reviews many actions and chooses the one which comes closest to achieving its goals, whereas the reflex agents just have an automated response for certain situations. 1.Goal-based agent focuses only on reaching the goal set and hence the decision taken by the agent is based on how far it is currently from the goal state.

2. The goal based action is intended to minimize this distance It means, i n each state it's only intention is to go close to the goal state and cross the distance towards the final destination. 3. Before selecting the right action, the agent explores all possible actions. 4. the agent is more flexible and the agent develops its decision making skill by choosing the right from the available options.

FIGURE -1

[Here, we can imagine a scenario like thisIn a situation(environment), there occurs an issue. A person(agent) senses those issues by his sensibility(sensors) and observes the situation(what the world is like now) to solve that. At first, the

person tries to recall(states) if he had faced this type of situation before? ? can we apply goal based agent in advance level ? does work with single goal or multiple goals ? what rules are used in GBA or if-then else ? Effectors

(how the world evolves)If yes then he tries to remember what was his action that time !(what my actions do) if not, then what should I do?(what it’ll be like if I choose action A) And will my this action change the situation?! (What  action should I take now?)  Somehow, the person gets the answer and using any kind of tool(effectors) he imposes this action to the situation for the betterment(effectors to the environment).] 

- Here, the agent senses the present situation by the sensors. - Present situation is represented by “what the world looks like?” - Exploring the available actions by “what’ll be like if I do action A?” - These 2 answers are covered by the state “how the world evolves?” - “What my actions do?” is defined according to the environment’s necessity. - Finally, it chooses the action which serves the goal.

Why goal-based agents? :

Although the goal-based agent does a lot more work than the reflex agent, this makes it much more flexible because the knowledge used for decision making is represented explicitly and can be modified.

Example : 1. If our mars Lander needed to get up a hill the agent can update it’s knowledge on how much power to put into the wheels to gain certain speeds, through this all relevant behaviours will now automatically follow the new knowledge on moving. However, in a reflex agent many condition-action rules would have to be re-written.

2. If it starts to rain, the agent can update its knowledge to change the duration of the application of brakes, thereby altering all the relevant behaviours to adapt to the new conditions. For the reflex agent, on the other hand, we would have to rewrite many rules to have the same effect. Similarly, a goal-based agent can easily be modified to reach the destination via a different route (maybe the path closest to the fuel station). The reflex agent’s rules work only for a particular route; they must all be replaced to change the route.

3. Alibaba expresses “G Plus” robots for testing to delivery at home. It is based on a goal based agent. How to deliver, where to deliver and which path should take all this planning made by a goal based agent.

? what could be the other examples of GBA ? Limitation of GBA

Agenda : A goal-based agent has an agenda, you might say. It operates based on a goal in front of it and makes decisions based on how best to reach that goal. Unlike a simple reflex agent that makes decisions based solely on the current environment, a goal-based agent is capable of thinking beyond the present moment to decide the best actions to take in order to achieve its goal. In this regard, a goal-based agent operates as a search and planning function, meaning it targets the goal ahead and finds the right action in order to reach it. This helps a goal-based agent to be proactive rather than simply reactive in its decision-making. You may take a goal-based approach to tasks at work. For example, you might set a goal for yourself to become a more efficient typist, which will help you in completing assignments more quickly. A step toward that goal, then, might be to enrol in a typing course or to devote 15 minutes a day to practice in order to increase your word count per minute. Your decisions are flexible, a hallmark of goal.

Goal-Based Agent Expansion : Goal-based agents expand on the concept of model-based agents because of the presence of the goal itself. A model-based agent uses percept history and internal memory to make sense of

the world around it. A goal-based agent takes this model one step further by implementing a desirable outcome, or goal, and then making decisions about how best to proceed toward it.

? difference between SRA and GBA ?...