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68 Cards in this Set

  • Front
  • Back
Tulving (1972, 1983) identified two seperate and distinct long term memory systems, these are...
1. Episodic
2. Semantic
The memory system that holds information about events in which you somehow participated is called
Episodic Memory
The memory system that holds information about general knowledge is called
Semantic Memory
Knowledge representation refers to how knowledge is _______ and the _______ that allow us to access and use this knowledge.
represented; processes
What are the two models of cognitive architecture?
Computational and Connectionist
Cognitive architecture refers to
the organisation of cognitive structures and the processes that work on them.
The computational model or ________ ________ approach of cognitive architecture are those in which _____ _________ processes operate over complex _______ ________ ________.
information processing;
rule governed;
symbolic mental representations.
The connectionist model or _____ ______ approach of cognitive architecture are those in which _________ is captured in patterns of ______ across a complex network of interconnected, ______ _____.
neural processing;
simple units.
Computational models of cognitive architecture are characterised by the following 3 things:
1. symbolic representation - abstract representations
2. local representation - reside in specific memory
3. serial processing - sequential
There are many types of knowledge that we retain, in general a distinction is made between two basic knowledge types these are:
1. Declarative Knowledge
2. Procedural Knowledge
Sternberg suggests that researchers differentiate between ________ based models and ____________ based models.
perception; meaning
Declarative Knowledge is knowledge about _____ such as facts, information and ideas and can be easily made explicit, ______ and described in _______, pictures or _______.
Procedural knowledge represents our knowledge of _____ we do things, and includes our abilities to perform both _____ and ______ tasks.
We studied 3 symbolic representation of declarative knowledge, these are
1. Concepts;
2. Propositions; and
3. Schemas.
Concepts are...
fundamental units of thought
Concepts help _____ the multitude of objects, events and _______ in our physical and ______ world, categorising them by similarity of their _____.
Concepts allow us _____ _ ______ by not having to represent each instance of the object eg a ball
economy of representation
Concepts embody knowledge about objects that is not _______ _______, eg snake knowledge
perceptually apparent
What are the two models of how conceptual knowledge is represented that we study?
Semantic networks & feature comparison models
A netowrk consists of ______ and _____.
nodes and links
Semantic networks describe the organisation of concepts in terms of a
network of associated concepts.
A nodes corresponds to a _____ or _____. The links designate the _______ between two _____.
Information is retrieved from the semantic network via the process of
Spreading activation
The semantic network approach has been successful in accounting for a number of findings such as the
typicality effect
The phenomenon in which experimental subjects are faster to respond to typical instances (robin is a bird) of a concepts that they are to atypical instances (penguin) is called the
typicality effect
Spreading activation refers to the
excitation of one node in a semantic network by the excitation of another node to which it is connected.
Declarative memory is _______ and consciously ________ whereas procedural memory is _______ represented and ___ _______ accessible.
not consciously.
Anderson ACT theory the interaction between...
working, declarative and procedural memory.
Working memory is that part of ______ memory that is highly ______ at any one time.
Proposition representation theories assert that knowledge is representations comprise ______, which are the _____ ___ of knowledge about which one can make true or false judgements.
smallest units.
Anderson model of cognitive architecture, the adaptive control of thought or _____ assumes the basic level of representation for events are ________.
Computational, rule-based systems use the logic of _______ calculus to compute meaning from a _______ structure, and make ________.
Propositional networks extract and represent meaning, while letting go of the
peripheral structure
In propositional representations a given fact is expressed in terms of a ________ which specifies the relationship between the associated concepts.
The representation of more complex information is thought to be achieved through the organisation of ideas according to a general knowledge structure called a
A schema can be viewed as a structure with several slots in which to
organise relevant information
Special kinds of schemas called ______ are thought to represent knowledge about routine everyday situations, by organising everyday information into ordered ________ of ______.
Sequences of events.
Schemas and scripts are important in providing organisational structure for complex knowledge but the recall of information based on general knowledge structures can lead to
memory distortions and incorrect inferences.
Bower (1979) showed that people remember ______ and may construct ____ ______ based on schemas and scripts. This has implications for the accuracy of _____ ______ ______.
False memories;
eye witness accuracy.
In contrast to computational/rule-based models, which were based on the information processing view of the way computers process information, the connectionist approach takes its inspirations from the way the
brain processes information.
Connectionist models represent knowledge as a
pattern of activation across the network.
In connectionist models cognitive processing occurs in ______ not ______.
The 4 basic principles/properties in the connectionist model are:
1. Neural network structure
2. Distributed representations
3. Spreading activation
4. Parallel Processing
Connectionist networks can have single or _____ layers. A single layer has an ______ unit connected to the _____ unit. In complex networks there can be _______units which act as an intermediary between input and output units.
In connectionist models distributed processing refers to the sum of all ______ units distributed across the ______ ______ of the network, where units represent ______-______ only.
output layer;
In spreading activation the connection strength is determined by the
statistical association between two units and the activation rule.
Connection units can be ______ or ______ and vary between ___ and ___.
+ 1.
A connection weight of 0 means
no activation between the connected units.
Statistical association happens when the output unit becomes
strongly associated with the input unit over time
The connectionist approach to cognitive architecture was inspired by the brain metaphor and neural processing but this approach was
not intended to be biologically faithful to the way the brain actually processes information.
In computational models, cognition involves the manipulation of complex symbolic representations Such as declarative eg. _____, _____ & ____, and procedural eg ____ & _____.
concepts, propositions & schemas;
conditions & actions.
McClellend described connectionism as "When an event is experienced, it creates a
pattern of activity over a set of processing units that is then considered a representation of the event"
The Transfer function is output =
sum of input times weight.
The mental process in the the computational model are _______ in nature and are limited by capacity constraints eg _____ ______
serial processing.
Knowledge representation in computational models features:
1. complex ________ representations
2. _______ representations
3. Constructed form combinations of _________ structures
4. are stored at _____ _______ in memory
1. mental
2. symbolic
3. propositional
4.specific loacations
Whch approach to cognitive architecture is regarded as better at accounting for knowledge represention.
Experts do not agree whether thecomputational or connectionist models are better.
4 of the main issues used to debate the relative merits of connectionist versus computational models are:
1. Learning
2. Retrieval
3. Structure of mental representations
4. Constraint satisfaction
In the computational model the goal of learning is to
formulate explicit rules (proposition, productions) and requires innate knowledge.
In the connectionist model the goal of learning is to find the right connection weights so that the correct pattern of activation is returned
connection weights so that the correct pattern of activation is returned
In Anderson's ACT model what are the three stages of procedural learning?
1. Cognitive Stage - learning explicit rules for procedures
2. Associative Stage - Strengthening associations through practice
3. Autonomous Stage - the new rules become implicit and automatic
The law of contiguity refers to the idea that
two events that occur closely together in time or space become associated with one another.
In connectionism the Hebb learning rule is when unit A and B are simultaneously activated this
increases the strength of connection between them in proportion with their joint activation.
In connectionism the Delta learning rule is superior to the Hebb rule as it accounts for ______.
In Delta learning in successive presentations the size of the error is _______, and the pattern of activation more closely resembles the ____pattern of activation.
Content addressability refers to the
natural account of certain attributes in human memory.
In a distributed system, target information can be retrieved by providing a _____ of the items _______. In contrast _________ representational system requires the knowledge of ______ __ _____ which requires a ______ search.
where to look;
A criticsim of the connectionism approach is that ideas are simply adding together individual units and do not account for ______ which governs the way ______ are combined in certain rule determined ways. ie Jack chases butterflies
Cognitive models need to allow for situations where making the correct response depends on
several conditions being met at the same time or parallel processing.