PSYCH 354- MIdterm #1 TXT Def

experimetnal psychology

study of psychological phenomena using experimental methods

• ex. a ressearcher wants to determine whether people rmeember pictures better than words

• contribited the use of experimental methods used to investigate cognition

fragmetnation

when a field becomes divided into multiple schools of thought, approaches, or research traditions that may disagree about how phenomena should be understood

• ex. when studying the concept of memory, researcher A thiks it s asystem of symbolic representations, while another thinks it emrgs from patterns of acticity acrtoss eural networks, and C thinks it depdens on persons body and env.→ while all r studying memory they all have diff assumptions abt what memory actually is

cognitie science

an interdiciplinary concept that deploys information processing as a common language. tries to understand the nature of cognition/human mind by bringing together multiple disciplines

• ex. if u want to understand language comprehension- u would turn to different disicpiines to explain ceratin things. use psych to perform experiments o how people understand sentences, linuuisties to discuss hteories of grammar and language structure….

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modern experimental psychology

• rooted in Wundts and Fechners publications

concsious experience

cybernetics

study of adaptive behavior of intelligent agents through notions of feedback and information theory

computational level

when formal proofs are used to determine what information processing problem is being solve

algorithmic level

when experimental observations and computer simulations are used to determine the particualr information processinf steps being used to solve the information processing problem

implementation level

biological or physical methods used to determenie the mechanistic principles that acutally instantiate the information processing steps

information processing

rule-governed symbol maniulations of the same type performed by a digital computer (classical cos sci interpretation)

digital computers

automatic symbol manipulators

• machines that manipulats symboliv representations by applying well-defied rules; thye brought symbolic logic to mechanized life

embodied cognitive science

abandoons mthadological solipusm

• reresentational states are individuated in terms of their relations to other represetnational states

• borrows ideas from cybernetics in that agents are adaptively linked to their enironment

• ex. an animals actions on the owrld can change the world, which in turn affects their later actions

sense-think-act cycle

defines there is no direct contact between sensing and acting

• thinking = representations, that have the task of planning action based on the sensed data

• represetnations stant between perceptual inputs and behavioural outputs

sesns-act processing

direct links between sensing and acting

• purpose of the mind is not to plan action, but instead to coordinate sense-act relations

• brain is a controler rather than a planner

information processing hypothesis

idea that cognition is a form of infromation processing— main idea that helped unify cog sci. something happens → inofrmation is recived/processed → some cognitive operation occurs → response occurs

• ex. u see a friend on campus→ u receive visual input, identify the person, decide whether to wave, wave. The info from ur environemnt is processed to produce behaviour

• this concep is what initially allowed researches form diff disciplines to communicate

classical cogntive science

vies cognition as rule-governed manipulation of symbols, similair to how digital computer processes symbolic infomatioin (symbols + rules + processing = cognition)

• ex. treating cognition like math→ attaching explicit rules to each symbol. Involves structured reperesntations being maipulated according to rules

• the first majr schoo of thought within cog sci and producesd important advances in areas

well-posed problem

includes a clearly defined knowledge state, goal state and defined operations for moving between states . Due to high specificity it can be repesented as a problem state that can be searched

• ex. chess- yk the board position, possible moves, the goal, nd the rules dictaing the moves. A computer an therefore search possuble moves though a problem space

• not as useful inn cog sci, as human minds and cognition are highly complex

ill-posed problem

ambigious and poorly defined knowledge states,goa state, ad the operations for manipulating knowledge. cannot easily define a probllem space for solving it

• ex.recognizing a friend in a crowd. You dont have any cleary defined steps, but rather u are abel to recognize the perso despite changes in lighting, angle, distance, facial expression, etc.

• difficulty of classical systems with things like speech recognition, vision, and walking helped motivate alternative approaches, particualry connectionism

connetionist cogntiive science

views acognition as emerging from networks of simpe neuron-like processing units that operte in parallel and learn though changes in their connections → main computational model is the artificail neural network (neurons + connections + learning = cognition)

• ex. training a e=neural network to distinguish cats form dogs→ network recieves many exampls and adjusts its connection weight sso that it graually beomes better at distingising catgeories

• provides a biolofically insired alt to the classical digital computer model- attempts to explain cognition using mechanisms that resemble properties f the brain