代写 Balancing Long-Term Reinforcement and Short-Term Inhibition

Balancing Long-Term Reinforcement and Short-Term Inhibition
Christian Lebiere (cl@cmu.edu) Carnegie Mellon University Bradley Best (bjbest@adcogsys.com) Adaptive Cognitive Systems

Outline
• Rational analysis of memory
• Computational implementation
• Long-term impact of short-term effects • Revisiting the environment
• Combining reinforcement and inhibition • Internal dynamics mirror environment
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Rational Analysis of Memory
• Humanmemoryhasadaptedthroughevolutionto the structure of its environment (Anderson & Schooler, 1991)
– Frequency effects – Recency effects
– Spacing effects
• Evenapparentfailuresserveafunctionalrole
– Forgetting as a way of managing scale of memory demands
• Givenresourceconstraintsonlong-termmemory, optimal behavior is making most available the memories that are most likely to be needed
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Power Law of Memory Retention and practice functions for range of measures
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P = AT−b
logP =logA−blogT

Power Law of the Environment
Need Odds follow power law in human environments: NYT headlines, CHILDES speech db, email addresses
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Computational Implementation • DelayandPracticeareroughlyadditiveeffects
• Activationaslogoddsmodulatesrecallandlatency
P r o b ∑n
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1−Prob=Odds=a tk−d 1
∑n  Ai =B+ln tk
 −d 1

In The Short Run
• “Apowerfunctionimpliesthattheperformance measure will go to infinity as time goes to zero.” p.398
• “Powerfunctionsforforgettingtendtobeobtained when we use measures that do not have upper bounds or do not approach their upper bounds.” p.398
• “Powerfunctionsseemtodescribememory performance from a few seconds to years.” p.398
• Whatarethelong-termimplicationsifperformance measures grow arbitrarily large under a few seconds?
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Winner-Take-All Dynamics
• Reinforcementleads to feedback loop
• Strongconditionson retrieval can help…
• Buttheydetractfrom the use of activation
• Needpartialmatchingandunder-constrainedretrievals
• Canbecontrolledbymodelerwithtagsorfinsts
• Metacognitiveknowledgehardtospecifyathigh-level
• Needrobust,generalmodelsofopen-endedbehavior
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Back to the Environment
• Languageaspreeminentsequentialstructuredenvt • Short-termdepressioninneedoddsatsmalllags
• Consistentacrossverydifferenttextcorpuses
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Words and Groups
• Thepatternholdsforhighestfrequencywords
• Additiveeffectisobservedatalllevelsoffrequency
• Peakinoddsboostconsistent~lag5-10forallgroups
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Access to Arithmetic Facts
• Asinoriginalanalysis,effectmustholdacrossdomains • Arithmeticdomaingeneratedfromvalidatedmodel
• Patternholdsincludingpeakandsizeofinhibition
• Applytootherenvironments,e.g.web,physicalspaces
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Activation Inhibition
n   −ds ∑−d  t 
B=log t −log1+ n ij j=1 ts
• Parameters:
– Inhibition scale ts – controls
period to peak reinforcement
– Inhibition decay td – specifies magnitude of inhibition effect
• Additive term integrates with other terms of activation equation: noise, spreading association, partial matching
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Emergent Robustness
• Soft inhibition differs from pathological behavior of the default version and from the hard and fixed round-robin of the finst version
• Running the retrieval mechanism unsupervised leads to the gradual emergence of an internal power law distribution internally
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Discussion
• Biologicalimplementationofshort-terminhibition
– Short-term depotentiation?
• Architecturalimplicationsofshort-terminhibition
– Working memory and refraction
• Contributionofothercognitivefactorsintask
– Grammatical rules, base-10 systems
– Could have evolved in response to cognitive limitations
• Integratecombinationofenvironmental,neuraland behavioral constraints in cognitive architectures
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