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recognizers aren t very tolerant of background noise, it still works more than 99% of the time. The trick isn t software with deep understanding of 800 numbers, but rather the structuring of the domain so that the task is within reach of the technology. The microworlds construct of the last chapter assists with this necessary systems engineering trickery. A wireless of ce assistant microworld consists of prototypical UKOs for address book, calendar, to-do list, formatting, and printing documents with UDHs to instantiate, constrain, and expand the UKOs per experience with the <User/>. Even unreliable speech recognition and extraction technology (e.g., name nders) with statistical <Topic/> spotting may enable an iCR to recognize user states needing the wireless of ce assistant, such as discovering BlueTooth from the user s laptop to synchronize address books autonomously ( Is the laptop turned on ). Problems like thrashing from one microworld to another (laptop to address book) need to be characterized and solved. Discovery of user intent remains a chronic problem. It will take not just natural language processing and computer vision, but also substantially evolved AML to gracefully and passively acquire relevant knowledge from users and to learn, again passively, what to do to actually help the user in the way the user wants to be helped.

The main idea is that the sending node computes an appropriate transmit power based on its traf c distance d and an estimate of the interference level it experiences, instead of collision avoidance information (CAI) advertised by neighboring nodes used in references 37 and 38 The power function, -PCS, is de ned as P (t) = Pmax (d/dmax ) , where dmax is the transmission range of Pmax , is a constant between 0 and , and is the power attenuation factor Each value corresponds to a different power control scheme, and in one scheme the value is uniform to all the nodes in the network By choosing an appropriate value of , this scheme can improve energy ef ciency and channel spatial reuse; furthermore, it yields a fair throughput distribution among different destination ranges.

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A cognitive assistant should focus on the following wireless (not of ce) tasks: 1. Perform wireless access tasks described at the <Information/> level of abstraction, such as Keep track of the weather or What s the weather going to be like in Boston 2. Notify the user of problems, such as inability to access or interpret <RF/> in a new scene. 3. Suggest alternate plans for addressing in a <Situation/> (<Scene/> plus user <Needs/>). (a) Explain steps required to execute a plan. (b) Justify plans in terms of QoI value added. 4. Competent mixed-initiative interaction: (a) Initiate dialog for autonomously sensed situation changes. (b) Explain reasoning for <Self/>-initiated actions (not stilted). (c) Answer informal questions about the wireless devices and networks. (d) Pose planning questions ( Can we move 500 meters that way ). 5. Reliably detect and predict user intent: (a) Continuously track stereotype scenario templates.

Simulation results show that -PCS can achieve improvement of over 40% in throughput, energy ef ciency by a factor of 3, and better fairness with respect to channel utilization Interference-Based MAC Schemes The power control algorithms discussed above can achieve good reduction in energy consumption However, it cannot improve the throughput This is because the exchange of RTS and CTS messages, which are used to silence neighboring nodes, prohibits potential concurrent transmissions in the neighborhood during the DATA/ACK packet transmission To increase spatial reuse, and thus increase the throughput, references 8 and 37 39 have proposed various interference-limited media access control algorithms In these algorithms, new transmission is admitted as long as it does not corrupt ongoing neighboring transmissions.

(b) Rectify decisions and actions against templates ( cases ). (c) Obey meta level commands ( Knock it off ). 6. Adapt to users: (a) Who regularly take apparently inappropriate actions. (b) Agent s scene perception must adapt to user actions. These very challenging prototypical tasks are common to the following cognitive wireless assistant use cases. 9.3.1 Zeus in a Box

The basic idea is that by exchanging collision avoidance information (CAI) in the control packet, nodes compute the maximum allowable power levels that will not corrupt any ongoing transmissions in the neighborhood, and then they use this power level as the upper bound of the transit power level for subsequent packet transmissions including the control packets This is completely different from the idea of collision avoidance in current carrier sensing medium access control algorithms, where nodes in the carrier sensing range of an ongoing transmission should defer their potential transmissions PCMA The Power Controlled Multiple Access Protocol (PCMA) [8] proposes a exible variable bounded-power collision suppression model with two separate channels (data channel and busy tone channel), which is generalized from the transmit-.

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