Auto Topic: gate
auto_gate | topic
Coverage Score
1
Mentioned Chunks
19
Mentioned Docs
1
Required Dimensions
definitionpros_cons
Covered Dimensions
definitionpros_cons
Keywords
gate
Relations
| Source | Type | Target | W |
|---|---|---|---|
| Auto Topic: gate | CO_OCCURS | Auto Topic: gates | 11 |
| Auto Topic: gate | CO_OCCURS | Auto Topic: terminals | 7 |
| Auto Topic: gate | CO_OCCURS | Logical Agents | 6 |
| Auto Topic: gate | CO_OCCURS | Propositional Logic | 5 |
| Auto Topic: gate | CO_OCCURS | Problem Formulation | 4 |
Evidence Chunks
| Source | Confidence | Mentions | Snippet |
|---|---|---|---|
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.67 | 8 | ... ignal(t) =1 ∨ Signal(t) =0 . 3. Connected is commutative: ∀t1,t2 Connected(t1,t2) ⇔ Connected(t2,t1) . 4. There are four types of gates: ∀g Gate (g) ∧ k = Type(g) ⇒ k = AND ∨ k = OR ∨ k = XOR ∨ k = NOT . 5. An AND gate’s output is 0 if and only if any of its inputs is 0: ∀g Gate ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.67 | 8 | ... ectors that control the flow of information in the LSTM via elementwise multiplication of the corresponding information vector: • The forget gate fdetermines if each element of the memory cell is remembered (copiedForget gate to the next time step) or forgotten (reset to zero). • ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.67 | 7 | ... rminal(Out(n,c))) ∧ (n> j ⇒ Out(n,c) = Nothing) 294 Chapter 8 First-Order Logic 11. Gates, terminals, and signals are all distinct. ∀g,t,s Gate (g) ∧ Terminal(t) ∧ Signal(s) ⇒ g ̸= t ∧ g ̸= s ∧t ̸= s . 12. Gates are circuits. ∀g Gate (g) ⇒ Circuit(g) Encode the specific problem in ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.65 | 6 | ... s, predicates, and constants to represent them. First, we need to be able to distinguish gates from each other and from other objects. Each gate is represented as an object named by a constant, about which we assert that it is a gate with, say, Gate(X1). The behavior of each gate ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.65 | 6 | ∃ n Signal (In(n,g)) =1 . 7. An XOR gate’s output is 1 if and only if its inputs are different: ∀g Gate (g) ∧ Type(g) =XOR ⇒ Signal(Out(1,g)) =1 ⇔ Signal(In(1,g)) ̸= Signal(In(2,g)) . 8. A NOT gate’s output is different from its input: ∀g Gate (g) ∧ Type(g) =NOT ⇒ Signal(Out(1,g) ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.57 | 2 | ... For example, an automated taxi might have the goal of taking a passenger from San Francisco to Marin County and might know that the Golden Gate Bridge is the only link between the two locations. Then we can expect it to cross the Golden Gate Bridge because it knows that that wil ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.57 | 2 | ... color, or cost of the various components are irrelevant to our analysis. If our purpose were something other than verifying designs at the gate level, the ontology would be different. For example, if we were interested in debugging faulty circuits, then it would probably be a go ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... s Ltd/Alamy Stock Photo; Autonomous cars: Andrey Suslov/Shutterstock; Atlas Robot: Boston Dynamics, Inc.; Berkeley Campanile and Golden Gate Bridge: Ben Chu/Shutterstock; Background ghosted nodes: Eugene Sergeev/Alamy Stock Photo; Chess board with chess figure: Titania/Shuttersto ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... rcuit’s functionality. For example, does the circuit in Figure 8.6 actually add properly? If all the inputs are high, what is the output of gate A2? Questions about the circuit’s structure are also interesting. For example, what are all the gates connected to the first input termi ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... igital circuits? For our purposes, they are composed of wires and gates. Signals flow along wires to the input terminals of gates, and each gate produces a signal on the output terminal that flows along another wire. To determine what these signals will be, we need to know how the ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... t output is the sum, and the second output is a carry bit for the next adder. The circuit contains two XOR gates, two AND gates, and one OR gate. Section 8.4 Knowledge Engineering in First-Order Logic 293 In(1,X1) to denote the first input terminal for circuit X1. A similar functi ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... o prove any outputs for the circuit, except for the input cases 000 and 110. We can pinpoint the problem by asking for the outputs of each gate. For example, we can ask ∃i1,i2,o Signal (In(1,C1)) =i1 ∧ Signal(In(2,C1)) =i2 ∧ Signal(Out(1,X1)) =o, which reveals that no outputs are ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... . In this example, planning and acting are interleaved; for example, one would defer the problem of planning the walk from the curb to the gate until after being dropped off. Thus, that particular action will remain at an abstract level prior to the execution phase. We defer disc ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... s graphics processing units (GPUs), tensor cores, tensor processing units (TPUs), and Section 29.2 AI Architectures 1069 field programmable gate arrays (FPGAs) are hundreds of times faster than conventional CPUs for machine learning training (Vasilache et al., 2014; Jouppi et al., ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... rd, K. M., 1057, 1095 Ford, L. R., 125, 1095 Ford, M., 46, 53, 1062, 1095 Index 1133 foreshortening, 989 Forestier, J.-P., 873,1095 forget gate (in LSTM), 826 Forgy, C., 329, 1095 formal logic, 26 Forrest, S., 161, 1106 Forster, E. M., 1062, 1095 Forsyth, D., 1021, 1023, 1031, 10 ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... hnig, J., 125, 189, 190, 1096 Gaˇsi´c, M., 588, 1117 Gasquet, A., 402, 1095 Gasser, L., 636, 1088 Gasser, R., 127, 1096 Gat, E., 986, 1096 gate (logic), 292 Gates, B., 51 gating unit (in LSTM), 826 Gatys, L. A., 1034, 1096 Gauci, J., 873, 1096 Gauss, C. F., 188, 515, 735, 1096 Ga ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... Z., 903, 1100 Ingham, M., 267, 1116 inheritance, 335, 347 multiple, 348 initial state, 83, 86, 123, 193, 363 initial state model, 482 input gate (in LSTM), 826 input resolution, 326 inside–outside algorithm, 891 instance (of a schema), 135 instance-based learning, 704, |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | 48 initial state, 83, 86, 123, 193, 363 initial state model, 482 input gate (in LSTM), 826 input resolution, 326 inside–outside algorithm, 891 instance (of a schema), 135 instance-based learning, 704, 704–706 instant runoff voting, 630 insurance premium, 525 integrated informatio ... |