The document discusses different types of agent structures and programs. It describes simple reflex agents that select actions based only on the current percept. Model based reflex agents maintain an internal state based on the percept history. Goal-based agents choose actions that achieve defined goals, while utility based agents aim to maximize utility or happiness across states. Learning agents can improve by making modifications based on feedback from experiences.

1. THE STRUCTURE OF AGENTSK.MAHALAKSHMI.,AP/CSEAPEC

2. THE STRUCTURE OF AGENTSAgent Program:It implements the agent function mapping percepts to actionsArchitecture:Agent program will run on some sort of computing device with physical sensors called architecture.Agent=architecture+programK.MAHALAKSHMI.,AP/CSE

3. THE STRUCTURE OF AGENTSAgent programs:The agent programs take the current percept as input from the sensors and return an action to the actuators.

4. The agent program takes just the current percept as input because nothing more is available from the envirnoment.

5. If the agent’s actions depend on the entire percept sequence, the agent will have to remember the percepts.K.MAHALAKSHMI.,AP/CSE

6. Continue…Four kinds of agent programs:Simple reflex agents

7. Model based reflex agents

8. Goal-based agents

9. Utility based agentsK.MAHALAKSHMI.,AP/CSE

10. Simple reflex agentsThese are simplest kind of agents that select actions on the basis of current percept, ignoring the rest of the percept history.

11. The agent program for a simple reflex agent in 2 state vacuum environment is as followsfunction Reflex-Vacuum-Agent( [location,status]) returns an actionif status = Dirty then return Suckelse if location = A then return Rightelse if location = B then return LeftK.MAHALAKSHMI.,AP/CSE

12. Simple reflex agentsfig: schematic diagram of a simplex reflex agentK.MAHALAKSHMI.,AP/CSE

13. Infinite loops are often unavoidable for simple reflex agents operating in partially observable environments.

14. Escape from infinite loops is possible if the agent can randomize its actions.K.MAHALAKSHMI.,AP/CSE

15. Model based reflex agentsK.MAHALAKSHMI.,AP/CSE

16. Model based reflex agentsThe most effective way to handle partial observability is for the agent to keep track of the part of the world it can’t see now.The agent should maintain some sort of internal state that depends on the percept history and thereby reflects at least some of the unobserved aspects of the current stateModel based agentThe knowledge about “how the world works” whether implemented in simple boolean circuits or in complete scientific theories is called model of the world.The agent that uses such a model is called a model-based agentK.MAHALAKSHMI.,AP/CSE