Study Notes Of Lectures On Markov Assumptions, Machine Learning, Brain Learning, Types Of Learning, Memory, And Qualia

769 words - 4 pages

Markov assumption = given the state, you dont need to know the pastRepresentationsDifferent degrees of specialization-Some neurons good at specific recognition, some better at generalIf you have neurons that combine and spread out, synthesis of neurons, not a separate neurons for each specific feature in the world-smaller amount of neurons to avoid exponentiallyBINDING PROBLEMMinimize connections in the brain-Modularity-Related areas are next to each otherMANY LEVELS TO THE BRAINWhat/where pathwaysSensory motorBrocas and Wernickes regionsHow memory worksDisruption of memory of letters by counting backwardsTransfer of info from STM to LTMHow emotion ties to different parts of ...view middle of the document...

Different parts of the brainLots of different sub modules and chunks of processingLife is way more complicated than explained in this courseLearningEvolution DarwinianOperant Conditioning PavlovianReasoning Popperian, Bayseian, logicDifferent modes of perceptionDidnt even cover logicComputers can do amazing things, but it doesnt feel impressive and as if they can think and are intelligentThe logical reasoning is the easy partThe hard part is perception and unconscious decision makingMANY FORMS OF LEARNINGHabituation (less response), habituate the external stimuli (scratchy sweater you ignore it) and the difference between Long Term PotentiationOperant/Pavlovian conditioning-US,CS,CR-SS vs SR, using experiments to understand itReinforcement learning (RL)-Rescorla-Wagner-Learning by surprise, blocking-Exploration vs exploitationHIPPOCAMPUS IN TAXI DRIVERS IN LONDON GROWS over time-birds, voles, taxi cab driversDont learn when no surpriseWhere different types of memory occur in the brainSemantic, episodic, and skillDifferent species of birds have diff hippocampi-birds of same size that travel more have larger hippocampi-probably from evolutionScalingAnother reason for modules, evolutionary benefit to separate modulesEach module can evolve on its ownEX: Watchmaker trying to assemble a watch, every 3 minutes, the phone rings and you lose apart the watch-if you have separate modules, put together each module separat...

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Study Notes Of Lectures On Markov Assumptions, Machine Learning, Brain Learning, Types Of Learning, Memory, And Qualia

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