[A]
[B]
[C]
[D]
[E]
[F]
[G]
[H]
[I]
[J]
[K]
[L]
[M]
[N]
[O]
[P]
[Q]
[R]
[S]
[T]
[U]
[V]
[W]
[X]
back propagation MLPs (multilayer perceptrons)
2nd
3rd
4th
5th
6th
7th
8th
backups reinforcement learning
2nd
3rd
backward connections
backward-chain interpreters hypothesize-test cycles
backward-chaining interpreters RBS interpreters
2nd
3rd
bagging DTs (decision trees)
2nd
ballistics shooting
batch algorithms
MLPs (multilayer perceptrons)
2nd
batch learning
batching embodied agents
behavior policies reinforcement learning
2nd
3rd
behavioral decomposition
behaviors
adaptive behaviors
AI engineering
debugging
2nd
design
2nd
3rd
4th
methodologies
2nd
problems
2nd
3rd
4th
5th
programming
testing
2nd
adaptive gathering behaviors reinforcement learning
2nd
3rd
architectures
emergent behaviors
2nd
3rd
4th
5th
affordance
2nd
broadcasting
environments
2nd
functionality
2nd
3rd
perception
evaluation
2nd
3rd
learning behaviors imitation
shaping
training
trial and error
learning systems
movement fuzzy set theory
2nd
3rd
4th
5th
6th
7th
8th
9th
10th
11th
12th
13th
14th
15th
16th
17th
18th
19th
20th
21st
objects
collecting
contraptions
2nd
3rd
criteria
2nd
3rd
specification
2nd
3rd
4th
5th
6th
7th
prediction of movement
2nd
responses designing
steering behaviors assumptions
2nd
fleeing
2nd
3rd
forced exploration
obstacle avoidance
2nd
3rd
4th
5th
6th
7th
8th
9th
10th
11th
obstacle avoidance algorithm
projecting targets
seeking
2nd
3rd
wandering
subsumption architecture
2nd
3rd
4th
5th
6th
tactical behaviors capability customization
2nd
3rd
4th
5th
strategic decision making
2nd
subsumption architecture
2nd
3rd
4th
5th
wall-following behaviors
2nd
3rd
believability AI importance of
bias perceptrons
binary strings classifiers
biological evolution
defensive actions application
2nd
3rd
4th
5th
evolutionary outline
2nd
fitness computations
2nd
3rd
genetic operators
2nd
3rd
4th
module design
2nd
3rd
4th
representation
2nd
3rd
4th
5th
6th
emotions
2nd
AI techniques
2nd
biological models
2nd
human/machine interaction
2nd
3rd
4th
genomics
2nd
3rd
4th
phenetics
2nd
reproduction
2nd
3rd
theory of evolution
2nd
3rd
biological parallels MLPs (multilayer perceptrons)
2nd
brains
2nd
3rd
neurons
2nd
3rd
biologically inspired models neural networks
2nd
Black & White
black box understanding
informal knowledge
2nd
software specification
theoretical analysis
2nd
3rd
4th
bodies classifiers
Boltzmann distribution
Boolean conditional test DTs (decision trees)
boosting DTs (decision trees)
2nd
bootstrapping reinforcement learning
2nd
bottom-up design
brains perceptrons
2nd
3rd
branches DTs pruning
2nd
3rd
DTs (decision trees)
broadcasting emergent behaviors
Brooks, Rodney
brute-force optimization perceptrons
2nd
3rd
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