1. MODEL-BASED REFLEX AGENT By: Thokozani W. Katulukira CIS-026-16 T.W. Katulukira (2019) 1

2. What’s a Reflex Agent? This is an agent that preforms tasks based on the environment and its Knowledge base( set of predetermined rules ). T.W. Katulukira (2019) 2

3. What’s a Model-base Reflex Agent? This is an agent that uses its percept history and internal Memory( internal state ) to make decisions, about an internal model of the world/environment. The internal memory allows the agent to store information about the environment.  The agent then uses the semi-subjective history to understand the environment better. T.W. Katulukira (2019) 3

4. Updating internal memory To update the internal memory 2 things are needed. a.Information on how the world evolves without the Agent. b.How the world reacts to the Agent’s actions. These facts can help the agent predict how the world may react. These facts are called models( hence the name ). T.W. Katulukira (2019) 4

5. How is it different from a Simple Reflex Agent? A simple reflex agent only operates on the current state of the environment. While the Model-based Agent can act with facts from pervious States the environment (experience). A simple reflex agent doesn’t compute complex computational problems, nor does it exhibit intelligence. Model based agents deals with Partial Accessibility, which the simple Reflex struggles with. T.W. Katulukira (2019) 5

6. MBR Agent T.W. Katulukira (2019) 6

7. Example(SELF DRIVING CARS) The car will need a 3D percept of the environment around it. This is done with the help of multiple sensors on the car to give detail percept  This will help the agent(car) to know how far obstacles are and what is around it etc. This is how the agent get a model of the world around it. This is save in the internal memory T.W. Katulukira (2019) 7

8. Continued How the Car makes decisions:  First, we need some information about how the world evolves independently of the agent—for example, that an overtaking car generally will be getting closer as time pass.  To know this the agent will compare the current percept to the previous one in the internal memory.  Second, we need some information about how the agent’s own actions affect the world—for example, that when the agent turns the steering wheel clockwise, the car turns to the right, or if it breaks it slows down.  This is also done by comparing the current percept to the previous one in the internal memory.  So rules can be set so that depending on these two facts the car should act in some way, for instance:  When there is a car is getting closer the agent must slow down by using the breaks to give way to the faster car. T.W. Katulukira (2019) 8

9. OBSTACLE DETECTION T.W. Katulukira (2019) 9

10. ANY QUESTIONS? T.W. Katulukira (2019) 10

11. REFERENCES https://www.machinedesign.com/motion-control/saved-sensor-vehicle- awareness-self-driving-age https://www.machinedesign.com/motion-control/saved-sensor-vehicle- awareness-self-driving-age http://digg.com/video/why-self-driving-cars-are-hard http://www.ques10.com/p/30196/explain-model-based-reflex-agent/ https://www.doc.ic.ac.uk/project/examples/2005/163/g0516334/mbra.html T.W. Katulukira (2019) 11