Spanning seven orders of magnitude: a challenge for cognitive modeling
نویسندگان
چکیده
منابع مشابه
Spanning seven orders of magnitude: a challenge for cognitive modeling
Much of cognitive psychology focuses on effects measured in tens of milliseconds while significant educational outcomes take tens of hours to achieve. The task of bridging this gap is analyzed in terms of Newell’s (1990) bands of cognition—the Biological, Cognitive, Rational, and Social Bands. The 10 millisecond effects reside in his Biological Band while the significant learning outcomes resid...
متن کاملModeling Biology Spanning Different Scales: An Open Challenge
It is coming nowadays more clear that in order to obtain a unified description of the different mechanisms governing the behavior and causality relations among the various parts of a living system, the development of comprehensive computational and mathematical models at different space and time scales is required. This is one of the most formidable challenges of modern biology characterized by...
متن کاملNumeric Reasoning with Relative Orders of Magnitude
In [Dague, 1993], a formal system ROM(K) involving four relations has been defined to reason with relative orders of magnitude. In this paper, problems of introducing quantitative information and of ensuring validity of the results in IR are tackled. Correspondent overlapping relations are defined in R and all rules of ROM(K) are transposed to R. The obtained system ROM(R) depends on two indepe...
متن کاملArithmetical Functions Iii: Orders of Magnitude
It may at first be surprising that this is a reasonable – and, in fact, vital – question to ask even for the “elementary” functions f for which we have found exact formulas, e.g. d(n), σ(n), φ(n), μ(n) (and also r2(n), which we have not yet taken the time to write down a formula for but could have based upon our study of the Gaussian integers). What we are running up against is nothing less tha...
متن کاملLearning values across many orders of magnitude
Most learning algorithms are not invariant to the scale of the signal that is being approximated. We propose to adaptively normalize the targets used in the learning updates. This is important in value-based reinforcement learning, where the magnitude of appropriate value approximations can change over time when we update the policy of behavior. Our main motivation is prior work on learning to ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Cognitive Science
سال: 2002
ISSN: 0364-0213
DOI: 10.1207/s15516709cog2601_3