Software Agent
인지 구조 4주차 : 제 1 발제 인지구조 / 발제자 : 최봉환
John R. Anderson,
"Human Symbol Manipulation Within
an Integrated Cognitive Architecture,"
Cognitive Science, vol. 29, no. 3, pp. 313–341, 2005
Outline
• Introduction
• ACT-R
• Use of brain imaging
• The capacity for re-representation: A uniquely human trait?
Introduction
• Overview of ACT-R theory
– illustrative application of it to algebra equation solving
• Algebra equation solving
– uniquely human cognitive activity
– "what is unique about human cognitive?"
• Comparing human brain with ACT-R
– preliminary mapping ACT-R component to brain
 functional fMRI
ACT-R Theory
• ACT-R
– Adaptive Control of Thought–Rational
= cognitive architecture
• Theory
– for "how human cognition works"
ACT-R Architecture
• Role
Input = Problem
representation
(3x - 5 = 7)
Output
(x=4)
massive parallelism &
central bottle neck
Mental
representation
(3x = 12)
Retrieve Critical
Information
(7+5=12)
Communication,
Procedural Control
Goal : Strategy decision
(unwind stratage)
Algebra equation manipulation
• Why algebra equation solving problem
– substantial complexity
– tractably characterized and studied
• unlike many human accomplishments
(cf : Natural language)
• Problem
–

– solved by unwind strategy
The ACT–R model
• General instruction
–


The ACT–R model : speedup
• Speedup
– Compilation
• collapse multiple steps
into single step
– Reduction of retrieval times
• subsymbolic learning
– instruction strongly encoded during day0
• arithmetic fact repeated  major learning happening at the symbolic level
– production rules
Regions of interest
Paretal
 problem state
or imaginal
motor
manual
prefrontal
 retrieval
Anterior cingulate
 goal
Caudate
 procedural
Measuring activity
• Measuring activity
– BOLD : blood-oxygen-level-dependent
• measure neural activity directly have been attempted
– profile of activity in modules

• t = time, s = scales the time,
a = determines the shape of BOLD response,
m = govern magnitude
• f(x) = engage function
Characterizing the differences among
the brain regions
Assessing goodness of fit
• Measure the degree of mismatch against the noise in the data
–

토의 제안
• 인간과 동일한 구조를 모사하는 것의 의미는?
– 인간과 동일할 필요가 있는가?
• 인간에게 원하는 것과 컴퓨터에게 원하는 것이 다를 것 같은데..
– 인간과 동일한 것을 증명할 필요는 있는가?
• 1+3 = 4 = 2+2=4라면 내부구조의 의미는?
• 성능은?
– 간단한 문제라서 잘 풀리는 것이 아닌지?
– 수학적인 문제 혹은 논리적인 문제에만 적용 가능한 건 아닌지
• 모호함에 대한 해결책은?
– ACT-R은 Deliberative Agent인듯한데 모호한 정의에 대한 묘사는 어떻
게?
– Goal based Agent로 구성되어 있는데 목적지는 어떻게 찾을 것인가?