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$(20$ pts$)$ WYSIWIS $("$What You See Is What I See"$)$ depicts agreement among distributed software

agents in a collaborative networked system: namely, what consistent values of shared data$/$state the

agents see at designated time$-$intervals $.$ Examples of shared state are: i$)$ location of robo$-$players &

ball in a soccer field; ii$)$ product inventory in an online store for shopping by customers; iii$)$ presence

of hostile object in a terrain under surveillance by drones. Suppose the agents agree on a value $V_t$ a time

$t-$ thereby triggering a collective action $A(V_t,t^{\text{'}})$ at time $t^{\text{'}}>t$ that persists for time$-$duration $($e$.$g$.,$

moving of items to a shopping cart in online purchase, kicking of ball in robot soccer game, taking of

terrain picture by a drone's on$-$board camera$).$ WYSIWIS enforces agreement among agents on a new

value of data$/$state $V_{t+}$ due to the action $A,$ where E$.$g$.,$~~$100$msec,$$~~$250$msec

for robo$-$soccer play actions; and $$~~$2sec,$~~$3sec$ for online purchase actions. For the WYSIWIS

concept, illustrate the truth or otherwise of the following statements:

$($i$)$: Agent$-$level policy in sharing the data$/$state: say, selfish versus accommodative behavior of the

agents ${?}^1,$ depends on the definition of actions $\{A\}$;

$($ii$)$: Enforcing cohesion among agents in attaining the system objectives $($e$.$g$.,$ scoring of goals to win

a soccer game$)$ depends on the action time $$;

$($iii$)$: Passage of time in the application occurs in uniform steps $$;

$($iv$)$: Time$-$granularity $$ depicts a possible inconsistency among agents over the time$-$interval $(t,t+).$

You may give suitable examples to corroborate your assertions.

${?}^1$ In an example of terrain surveillance by multiple drones, a selfish behavior occurs when all the drones individually take

picture of a hostile object without any coordination; whereas, an accommodative behavior occurs when, say, only one or two

drones take picture and then share it with the other drones $($for further processing$).$ Here, the selfish behavior can drain out

the on$-$board battery energy $-$ due to the energy expended in unnecessarily taking more pictures than needed. Whereas, the

accommodative behavior can conserve the battery energy due to the turn$-$taking among drones. This policy choice of programmed

in the software agents $($running on drones$)$ impacts the longevity of surveillance mission $-$ and hence the mission success. A

drone without on$-$board battery energy is useless $!!$