Saturday, January 12, 2013

Genuine Bus Conductor


                       This is an another answer for a Assignment given by the same lecturer (Dr.Vlad). but this is somewhat different than previous one this will describe the environmental affection and relational agent aspects of the robot. This is an idea generated by dearest Girlfriend for our group. 

Rational Agent – Genuine Bus Conductor 

                 In  artificial  intelligence,  an  intelligent  agent  is  an  autonomous  entity  which  observes  through sensors  and  reacts  according  to  the  changes  of  the  environment  using  actuators.  It  directs  its activity towards achieving goals.  
                      In  our  day  today  life,  we  have  met  several  kinds  of  bus  conductors.  Bus  conductor  is  a  very important  character  for public  transportation.  We  decide  to  implement  a  bus  conductor,  who has  some  of  the  common  characteristics  of  modern  bus  conductors  and  avoiding  some disgusting features of them. Therefor we call this as a genuine bus conductor. 
                    Here, the bus conductor gives your bus ticket by listening to your destination and he gives your balance  correctly  at  that  moment  without  any  delay.  In  Modern  Sri  Lanka,  most  of  the passengers have to beg for getting their balance from the bus conductors. This agent avoids this problem.  This  genuine bus  conductor  can  shout by  revealing  their  destination  “ Maharagama, Nugegoda and Colombo. Come  and  get on the bus. There are more seats available” like other bus  conductors  in  Sri  Lanka.  He  can  identify  the  frauds  and  oppression  through  his  camera which  can  occur  inside  the  bus  such  pick  pockets  etc.  and  he  can  draw  attention  of  others towards that fraud.  If a passenger blame to the bus conductor for unreasonable matter, he can blame “You are an idiot .You are telling nonsense. Are you mad?” like other bus conductors in Sri Lanka. 

Task environments which relevant to genuine bus conductor

  1. Performance  Measure  –  Issuing  the  bus  ticket  of  correct  destination,  giving balance  without  delay,  identifying  the  paid  customers  and  remaining. And identification of frauds inside the bus. (We  can  insert  a  ticketing  machine  and  safe  easily  as  inbuilt  facilities  of  Robot.  Its stomach  will  be  the  safe  and  mouth  will  be  the  printer  and  money  input.it  will devour  the  money  and  easily  print  the  ticket  form  his  mouth.  And  also  this  is  very safety method. If some frauds try to maraud the money simply robot can run away) 
  2. Environment – Inside the bus and 100 square meters area around the bus. 
  3. Actuators  – issue bus tickets,  draw customers, make aware of others about the frauds, which occur inside the bus. 
  4. Sensors – voice of the passenger, camera, pressure, gravity.
                   The environment of this agent may be partially observable and stochastic because camera may not be identified some frauds which are missed from the sensor data. In bus conductor’s environment  avoiding  frauds  and  giving  balance  without  delay  maximize  the  performance measure of all agents, so it is  a partially cooperative multi agent environment. Especially in sri lanka, it must have ability to identify passengers foot in order to avoiding tread. If not definitely robot will be genuinely get punished from ladies.  This is  an episodic environment because the next episode does not depend on the actions taken in previous episodes.  Known environment can be seen there since all possible outcomes for all actions are given. 
               “Genuine  conductor”  is  playing  goal  based,  model  based  and  learning  agent’s  rolls simultaneously.  It  needs  to  be  learning  from  day  today  things  which  happen  to  it  (Eg  How  to stand  stably  when  bus  is  running  on  different  angles  and  different  bends).  And  also  he  needs much more powerful problem generating algorithm. Because it needs to deal with various kind of peoples who has complex behavior styles (Peoples who have different verbal skills EG. Tamil people’s  English  pronunciation  is  more  differ  than  Singhalese).  Learning  elements  will  be benefited persons feedback and sensor responses for this scenario.

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