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Rule-based inference systems employ a global representation of the problem space such as a blackboard or game board [12] and use condition action rules (IF THEN) that work well in closed-world applications like board games, where the state of the board changes, but the size of the board and the legal moves do not change during a game. Extensible rule bases add legal moves during a game. In open settings like medical diagnoses or autonomous adaptation to the in nite variety of quirks of wireless PDA users, the size of the game board of relevant knowledge is continually growing in some ways and shrinking in others (e.g., as constraints are discovered). As radio spectrum-use policy evolves and new downloads become available, new legal moves are constantly being added to the SDR repertoire. As consumers introduce new electronic systems equipped with these new <RF/> capabilities, the ways in which the <User/> can employ them explode exponentially. The CRA addresses such open domains as a discovery game board. The rules may consist of embedded rule bases, PROLOG logic bases, and autonomously acquired serModels with substantial <Self/> modi cation. This section introduces such autonomous extensibility in the extensible rule base of Tieresias. An illustrative rule from Tieresias is If the gram-stain (attribute) of the culture (entity) is negative (value of gram-stain attribute) & context then disease might (20%) be E. coli (classi cation decision)

400 350 300 250 200 150 100 50 0 0 0.1

It would have been a monster trade I really stepped on my own foot on that one Ride your profits, Harry That s the lesson here Learn to ride your profits (see Figure 52)..

Non adaptive Protocol (S = 50 ms, CP = 50 ms) Non adaptive Protocol (S = 25 ms, CP = 75 ms) Adaptive Protocol (Uth = 0.5, K = 2) Adaptive Protocol (Uth = 0.3, K = 2) Optimal Adaptation Power Consumption Lower Bound

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Here the game board consists of clinical information about patients and the related diagnostic conclusions of medical professionals. The rule uses the entity-attribute-value model of object-oriented behavior. The conjunction & context assures that the rule res using the data from the current patient. Tieresias top-level control system continually accesses the patient database to infer the identity of a bacterial infection of the blood. Such rules can be implemented as objects themselves with condition action slots and corresponding methods or attached procedures that perform the inferences, test conditions, and assert an inference. In Mycin, the rules were implemented by computer scientists interacting with medical doctors in the process now widely known as knowledge engineering. Tieresias enhanced Mycin to interactively acquire incremental knowledge beyond core Mycin [318]. Tieresias interpreted medical data from expert users, lab technicians, and medical doctors just like Mycin, but synthesizing automatic knowledge acquisition. Mycin applied facts and rules to deduce likely causes for symptoms, but Tieresias used abstractions of rules to guide the acquisition of new rules. The rule models were schemata, declaratory data structures that could be interpreted algorithmically to acquire new rules without further programming, theoretically from nonexpert users. The Identity-Schema de nes an organism in the open world of Tieresias. As shown in Figure 11-3, the acquisition of the identity, for example, of an

Compared with the xed subframe case, the adaptive protocol adapts the CPsubframe duration based on traf c loading. In Figure 12.8 we compare the power and delay performance for the 0.3 and 0.5 Uth cases. It can be seen that the case corresponding to Uth set to 0.5 has a signi cantly better SMAP power consumption for almost all the interarrival rates considered when compared to the case of Uth set to 0.3. This is true because larger values of normalized utilization (U(i)) are needed before the algorithm responds by increasing the CP-boundary. In Figure 12.8 we

Identity-Schema PrintName (Atom AskIt) Value (PrintName InSlot) PropertyList ((InstanceOf (Identity-Schema GivenIt) Synonym ((Kleene (10) <Atom>) AskIt) Description (String AskIt) Author (Atom FindIt) Aerobicity ((Kleene . . . AskIt) GramStain (GramInstance AskIt) Morphology (MorphInstance AskIt) Date (Integer Create) Create} Updates (AddTo (AND Organisms)) Instances (Acinetobacter, . . . Yersina) StringTranslation The identity of an organism Father Value-Schema Offspring Nil Description the Identity-Schema describes the format for an organism Author Davis Date 1115 InstanceOf Schema-Schema FIGURE 11-3 Identity-Schema de nes the data structure for an organism.

Non adaptive Protocol (S = 50 ms, CP = 50 ms) Non adaptive Protocol (S = 25 ms, CP = 75 ms) Adaptive Protocol (Uth = 0.5, K = 2) Adaptive Protocol (Uth = 0.3, K = 2) Mean Delay Lower Bound

question of how much he can make from trading down the road, if he can prove that he can do it now GINI: That makes sense Trade with as little money as possible now, while he is still learning to trade ME: And learning to be responsible with the money If I lose five thousand dollars more, at least we know that I can stay at Wakeman for a while longer In a way, it s money that we can afford to lose HARVEY: There is no such thing as money that you can afford to lose GINI: [silence] ME: [silence] HARVEY: Do you move into an apartment, and say to each other, well, it s okay if the apartment burns down We re only going to move into apartments that we can afford to burn down ME: No HARVEY: Your trading account is your next apartment.

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