AI - a Guide to Intelligent Systems.pdf - Member of EEPIS

Index
A
accelerated learning 185–8
accidental property 140
action, see rule, consequent
action potential 166
activation function 169
bell 278
hard limit 169
hyperbolic tangent 185
linear 169–70
saturated linear 189
sigmoid 169–70, 177
sign 169, 189
step 169
activation level 168
activity balance point 202
activity product rule 201
generalised 202
adaptive learning rate
186–8
adaptive neuro-fuzzy inference
system 277, 346
architecture 277–9
defuzzificztion layer 279
fuzzification layer 278
input layer 278
normalisation layer 279
rule layer 278–9
summation neuron 279
learning 280–2
adaptive topology 220
Advice Taker 6
aggregate fuzzy set 110–11
aggregation 110, 137
AI, see artificial intelligence
AI ‘winter’ 12
algebraic sum, see probabilistic OR
algorithm 34
a-kind-of, see is-a
AND 172
AND product 109
Anderson C. 13
ANFIS, see adaptive neuro-fuzzy
inference system
ANN, see artificial neural network
antecedent, see rule, antecedent
a-part-of 137–8
approximate reasoning 262–3
artificial intelligence 2, 6, 260
foundations 5–6
history 5–17, 19–20
paradigm shift 9
artificial neural network 12–13, 167
ASCII code 304
association 137–8
associative memory 187
associativity 100–1
attribute 131
Automatic Computing Engine 2
axon 166
B
Bäck, T. 289
back-propagation, see back-propagation
algorithm
back-propagation algorithm 13, 179–80
backward chaining 38–40
BAM, see bidirectional associative memory
Barto, A. 13
BASIC 30, 32
Bayes, T. 60
Bayesian reasoning 61–3, 65–72
Bayesian rule 60–1, 73
bell activation function 278