Posts Tagged: modeling

Paper: Melioration as rational choice

Maximization (…) is not a general explanatory principle for behavior. (…)
Melioration (…) is the dynamic process controlling allocation of time across response alternatives.
Herrnstein & Vaughan (1980). Melioration and behavioral allocation, p. 143+172


Chris R. Sims, Hansjörg Neth, Robert A. JacobsWayne D. Gray

Melioration as rational choice: Sequential decision making in uncertain environments

Abstract:  Melioration — defined as choosing a lesser, local gain over a greater longer term gain — is a behavioral tendency that people and pigeons share.  As such, the empirical occurrence of meliorating behavior has frequently been interpreted as evidence that the mechanisms of human choice violate the norms of economic rationality.  In some environments, the relationship between actions and outcomes is known. In this case, the rationality of choice behavior can be evaluated in terms of how successfully it maximizes utility given knowledge of the environmental contingencies.  In most complex environments, however, the relationship between actions and future outcomes is uncertain and must be learned from experience.  When the difficulty of this learning challenge is taken into account, it is not evident that melioration represents suboptimal choice behavior. 

Paper: Competitive mate choice

Hansjörg Neth, Simeon Schächtele, Sulav Duwal, Peter M. Todd

Competitive mate choice: How need for speed beats quests for quality and harmony

Abstract:  The choice of a mate is made complicated by the need to search for partners at the same time others are searching. What decision strategies will outcompete others in a population of searchers? We extend previous approaches using computer simulations to study mate search strategies by allowing direct competition between multiple strategies, evaluating success on multiple criteria. In a mixed social environment of searchers of different types, simple strategies can exploit more demanding strategies in unexpected ways. We find that simple strategies that only aim for speed can beat more selective strategies that aim to maximize the quality or harmony of mated pairs.

Paper: Arithmetic with Arabic vs. Roman numerals


… how information is represented can greatly affect how easy it is
to do different things with it. (…) it is easy to add, to subtract,
and even to multiply if the Arabic or binary representations are used,
but it is not at all easy to do these things — especially multiplication —
with Roman numerals.  This is a key reason why the Roman culture failed
to develop mathematics in the way the earlier Arabic cultures had.
D Marr (1982): Vision, p. 21

[Copyright neth.de, 2008]:

Dirk Schlimm and Hans Neth (2008).

Modeling ancient and modern arithmetic practices: Addition and multiplication with Arabic and Roman numerals. Paper presented at CogSci 2008.


Dirk Schlimm, Hansjörg Neth

Modeling ancient and modern arithmetic practices: Addition and multiplication with Arabic and Roman numerals

Abstract:  To analyze the task of mental arithmetic with external representations in different number systems we model algorithms for addition and multiplication with Arabic and Roman numerals.  This demonstrates that Roman numerals are not only informationally equivalent to Arabic ones but also computationally similar — a claim that is widely disputed.  An analysis of our models’ elementary processing steps reveals intricate trade-offs between problem representation, algorithm, and interactive resources.  Our simulations allow for a more nuanced view of the received wisdom on Roman numerals.  While symbolic computation with Roman numerals requires fewer internal resources than with Arabic ones, the large number of needed symbols inflates the number of external processing steps.

Paper: Discretionary interleaving and cognitive foraging


(…) we make search in our memory for a forgotten idea, just as we rummage our house for a lost object.  In both cases we visit what seems to us the probable neighborhood of that which we miss.  We turn over the things under which, or within which, or alongside of which, it may possibly be;
and if it lies near them, it soon comes to view.
William James (1890), The Principles of Psychology, p. 654

[Copyright neth.de, 2007–2014]:

Steve Payne, Geoff Duggan, Hans Neth (2007).

Discretionary task interleaving: Heuristics for time allocation in cognitive foraging.

Journal article in JEP:G.

Stephen J. Payne, Geoffrey B. Duggan, Hansjörg Neth

Discretionary task interleaving: Heuristics for time allocation in cognitive foraging

Abstract:  When participants allocated time across 2 tasks (in which they generated as many words as possible from a fixed set of letters), they made frequent switches.  This allowed them to allocate more time to the more productive task (i.e., the set of letters from which more words could be generated) even though times between the last word and the switch decision (“giving-up times”) were higher in the less productive task.  These findings were reliable across 2 experiments using Scrabble tasks and 1 experiment using word-search puzzles.  Switch decisions appeared relatively unaffected by the ease of the competing task or by explicit information about tasks’ potential gain.  The authors propose that switch decisions reflected a dual orientation to the experimental tasks.  First, there was a sensitivity to continuous rate of return — an information-foraging orientation that produced a tendency to switch in keeping with R. F. Green’s (1984) rule and a tendency to stay longer in more rewarding tasks.  Second, there was a tendency to switch tasks after subgoal completion.  A model combining these tendencies predicted all the reliable effects in the experimental data.