IN2222 CogSys at TU München

Flashcards and summaries for IN2222 CogSys at the TU München

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Study with flashcards and summaries for the course IN2222 CogSys at the TU München

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

What is Hebbian Learning?

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

Spike Timing Dependent Plasticity: 

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

What are the functional implications of STDP? 

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

What is short term plasticity (STP) ?
Explain also the two types:

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

What is the motivation behind reinforcement learning? 

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

3 different implementation strategies of RL:        

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

What is a cognitive Architecture? Definition!    

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

Cognitivist cognitive architectures:

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

Emerging cognitive architectures:     

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

Requirements for Cog. Architectures:
 - Behavioral Characteristics:

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

How are the following components of a biological neuron modeled in the Spiking Neuron Models?
1. cell Membrane
2. different types of ions
3. opening and closing of ion channels

Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

Describe how the biological properties of a Neuron are represented in the Hodgkin-Huxley Model
1. Cell membrane
2. Nest Potential
3. Ion channels

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Exemplary flashcards for IN2222 CogSys at the TU München on StudySmarter:

IN2222 CogSys

What is Hebbian Learning?
- Two cells are near and repeatedly or persistently take part in firing it
--> growth process/metabolic change takes place
--> leads to higher efficiency in ones of the cells in firing them
- it is a unsupervised local learning rule (reinforces causal correlations)
- "What fires together, wires together " 

IN2222 CogSys

Spike Timing Dependent Plasticity: 
- temporally asymmetric form of Hebbian Learning by tight temporal correlations between the spikes of neurons
- rules for pairs and triples of spikes

- Long Term Potentiation: Causal Spike timing (presynaptic before postsynaptic)
--> strengthenening of synptic efficacy

- Long term Depression: Acausal Spike timing (postsynaptic before presynaptic spike)
--> weakening of the synaptic efficacy


IN2222 CogSys

What are the functional implications of STDP? 
- Correlation detection in spike trains
- Latency reduction
- temporal coding (tuning synaptic connections for sound source localization)
- Rate normalization

IN2222 CogSys

What is short term plasticity (STP) ?
Explain also the two types:

- synaptic plasticity in individual synapses
- based on history of synaptic activity

Short term Depression:
- decrease of synaptic efficacy during ongoing synaptic signaling due to depletion of neurotransmitters

Short term Facilitation (STF):
- increase of synpatic efficacy by influx of calcium into the axon after spike generation
more calcium results in higher release of neurotransmitters

IN2222 CogSys

What is the motivation behind reinforcement learning? 
in real world problems it is easy to decide if the task was accomplished successfully
but hard to determine the solution
--> reeinforcement learning

IN2222 CogSys

3 different implementation strategies of RL:        
- Dynamic Programming (MDP is fully known)
- Monte Carlo Method (dynamics of MDP are unknown)
- Temporal Difference Learning (Dynamic programming for MDPs with unknown dynamics)

IN2222 CogSys

What is a cognitive Architecture? Definition!    
Is the overall essential structure of domain-generic cognitive model, used for multiple-level analysis of cognition. Its function is to provide a essential framework to facilitate more detailed modeling of the mind. 

IN2222 CogSys

Cognitivist cognitive architectures:
Models those aspects of cognition that are independent from the task and constant over time
- only basic components and processes such as memory, knowledge representation
- generic model reflects set of assumptions
- framework without any domain knowledge

IN2222 CogSys

Emerging cognitive architectures:     
Framework that facilitates(erleichtern) development
- it models phylogenetic configuration of a newborn agent without requirement for functional modularity
- architecture is instantiated through acquisition of experience
- result: architecture can change over time


IN2222 CogSys

Requirements for Cog. Architectures:
 - Behavioral Characteristics:
- Reactivity: quick reactions through immediate and fixed responses

- Sequentiality:
activities are executed sequentially step by step over a certain timespan

- Routineness:
learning, adaption, and execution of reoccurring action patterns by trail and error

IN2222 CogSys

How are the following components of a biological neuron modeled in the Spiking Neuron Models?
1. cell Membrane
2. different types of ions
3. opening and closing of ion channels
1. Capacitor
2. electrical currents
3. change of conductance values (inverse of resistance)

IN2222 CogSys

Describe how the biological properties of a Neuron are represented in the Hodgkin-Huxley Model
1. Cell membrane
2. Nest Potential
3. Ion channels
Cell Membrane -> capacity C and restistance R

Nest Potential -> emulated by battery

Ion channels -> three components I(k) 

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