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cognitive science, connectionist models - Coggle Diagram
cognitive science
A Dynamic System Approach
features
state variable
continuous tume evolution
feedback and intrection
cognition through the dynamic lens
traditional view
dyanmic view
core concepts
state space
attractors
trajectory
non - linearity
application
motor devlopment
language processing
decision making
challenges
complexity
limited interpretability
integration issues
emprical validation
cognitive models
symbolic models
declearative models
knowledge representation
sematic networks
frames
inference machanism
forward chaining
backward chaining
logic
pradicate logic
first oder logic /pradicate logic
applications
expert systems
NLP
cognitive robotics
arcitectures
ACT-R (adeptive control of thought -rational
SOAR
challanges
scalability
complexity
incomplete knowledge
inference efficiency
hybrid models
components
units(nodes)
connections
activation ffunctions
learning rules
delta rule
backpropagation
hebbian learning
computational model of episodic and samentic memory
memory
explicit
episodic
semantic
implcit
skulls
priming
classical conditioning
others
connectionist models
advantages
biological plausibility
robustness
adaptivibility
scalibilty
limitations
interpretaion
overfitting
computational intensity
limited symbolic reasoning
learnings
hebbian learning
error correctin learning
unsupervised learning
applications
language proccessing
visual recognition
decision making
feed forward
recurrent model
self organised model
deep learning models