Simple Associative Model Research Articles

Don't throw the associative baby out with the Bayesian bathwater: Children are more associative when reasoning retrospectively under information processing demands.

Causal reasoning is a fundamental cognitive ability that enables individualsto learn about the complex interactions in the world around them. However, the mechanisms that underpin causal reasoning are not well understood. For example, it remains unresolved whether children's causal inferences are best explained by Bayesian inference or associative learning. The two experiments and computational models reported here were designed to examine whether 5- and 6-year-olds will retrospectively reevaluate objects-that is, adjust their beliefs about the causal status of some objects presented at an earlier point in time based on the observed causal status of other objects presented at a later point in time-when asked to reason about 3 and 4 objects and under varying degrees of information processing demands. Additionally, the experiments and models were designed to determine whether children's retrospective reevaluations were best explained by associative learning, Bayesian inference, or some combination of both. The results indicated that participants retrospectively reevaluated causal inferences under minimal information-processing demands (Experiment 1) but failed to do so under greater information processing demands (Experiment 2) and that their performance was better captured by an associative learning mechanism, with less support for descriptions that rely on Bayesian inference. RESEARCH HIGHLIGHTS: Five- and 6-year-old children engage in retrospective reevaluation under minimal information-processing demands (Experiment 1). Five- and 6-year-old children do not engage in retrospective reevaluation under more extensive information-processing demands (Experiment 2). Across both experiments, children's retrospective reevaluations were better explained by a simple associative learning model, with only minimal support for a simple Bayesian model. These data contribute to our understanding of the cognitive mechanisms by which children make causal judgements.

The pigeon as a machine: Complex category structures can be acquired by a simple associative model

Never known for its smarts, the pigeon has proven to be a prodigious classifier of complex visual stimuli. What explains its surprising success? Does it possess elaborate executive functions akin to those deployed by humans? Or does it effectively deploy an unheralded, but powerful associative learning mechanism? In a series of experiments, we first confirm that pigeons can learn a variety of category structures- some devised to foil the use of advanced cognitive processes. We then contrive a simple associative learning model to see how effectively the model learns the same tasks given to pigeons. The close fit of the associative model to pigeons' categorization behavior provides unprecedented support for associative learning as a viable mechanism for mastering complex category structures and for the pigeon's using this mechanism to adapt to a rich visual world. This model will help guide future neuroscientific research into the biological substrates of visual cognition.

Simulating the Acquisition of Verb Inflection in Typically Developing Children and Children With Developmental Language Disorder in English and Spanish.

Children with developmental language disorder (DLD) have significant deficits in language ability that cannot be attributed to neurological damage, hearing impairment, or intellectual disability. The symptoms displayed by children with DLD differ across languages. In English, DLD is often marked by severe difficulties acquiring verb inflection. Such difficulties are less apparent in languages with rich verb morphology like Spanish and Italian. Here we show how these differential profiles can be understood in terms of an interaction between properties of the input language, and the child's ability to learn predictive relations between linguistic elements that are separated within a sentence. We apply a simple associative learning model to sequential English and Spanish stimuli and show how the model's ability to associate cues occurring earlier in time with later outcomes affects the acquisition of verb inflection in English more than in Spanish. We relate this to the high frequency of the English bare form (which acts as a default) and the English process of question formation, which means that (unlike in Spanish) bare forms frequently occur in third-person singular contexts. Finally, we hypothesize that the pro-drop nature of Spanish makes it easier to associate person and number cues with the verb inflection than in English. Since the factors that conspire to make English verb inflection particularly challenging for learners with weak sequential learning abilities are much reduced or absent in Spanish, this provides an explanation for why learning Spanish verb inflection is relatively unaffected in children with DLD.

Inference in the Wild: A Framework for Human Situation Assessment and a Case Study of Air Combat.

Situation awareness is a key construct in human factors and arises from a process of situation assessment (SA). SA comprises the perception of information, its integration with existing knowledge, the search for new information, and the prediction of the future state of the world, including the consequences of planned actions. Causal models implemented as Bayesian networks (BNs) are attractive for modeling all of these processes within a single, unified framework. We elicited declarative knowledge from two Royal Australian Air Force (RAAF) fighter pilots about the information sources used in the identification (ID) of airborne entities and the causal relationships between these sources. This knowledge was represented in a BN (the declarative model) that was evaluated against the performance of 19 RAAF fighter pilots in a low-fidelity simulation. Pilot behavior was well predicted by a simple associative model (the behavioral model) with only three attributes of ID. Search for information by pilots was largely compensatory and was near-optimal with respect to the behavioral model. The average revision of beliefs in response to evidence was close to Bayesian, but there was substantial variability. Together, these results demonstrate the value of BNs for modeling human SA.

Reasoning about redundant and non-redundant alternative causes of a single outcome: Blocking or enhancement caused by the stronger cause.

Perceptions of the effectiveness of a moderate probabilistic cause are influenced by the presence of stronger alternative causes. One important idea is that this influence occurs because the strong cause renders the weaker one statistically redundant. Alternatively, the causes might be contrasted to each other, so the stronger cause may simply overpower perceptions of the weaker one. Causes may have the same polarity (e.g., two generative/excitatory causes or two preventive/inhibitory causes) or be of opposite polarity (e.g., a generative cause versus a preventive or inhibitory cause). Previously, we found that the presence of a stronger redundant alternative cause of the same polarity reduces causal judgements of the moderate cause (i.e., blocking occurs) but a stronger cause of the opposite polarity enhances judgements of the moderate cause (i.e., enhancement). Experiments 1 and 2 further explored these cue competition effects with redundant and non-redundant alternative causes (i.e., correlated versus independent alternatives). We generally found that blocking and enhancement occur with both redundant and non-redundant alternative causes. This is inconsistent with an information processing view of cue competition that relies on statistical redundancy to account for blocking. Although these results are inconsistent with a redundancy information processing account of cue competition and are consistent with our earlier contrast account, we demonstrate here that a simple associative model can account for the sometimes apparently contradictory effects of cue competition.

Graph-Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory.

We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over-predicted clustering in the norms, whereas the associative model under-predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and others on an associative network (POC) successfully predicted all of the network properties and predicted a word's top five associates as well as or better than the better of the two constituent models. The results suggest that participants switch between a contextual representation and an associative network when generating free associations. We discuss the role that each of these representations may play in lexical semantic memory. Concordant with recent multicomponent theories of semantic memory, the associative network may encode coordinate relations between concepts (e.g., the relation between pea and bean, or between sparrow and robin), and contextual representations may be used to process information about more abstract concepts.

Examining How Adding a Booster to a Behavioral Nutrition Intervention Prompts Parents to Pack More Vegetables and Whole Gains in Their Preschool Children's Sack Lunches

Data from a five-week intervention to increase parents’ packing of vegetables and whole grains in their preschool children's sack lunches showed that, although changes occurred, habit strength was weak. To determine the effects of adding a one-week booster three months post-intervention, children's (N = 59 intervention and 48 control) lunches were observed at baseline (week 0), post-intervention (week 6), pre-booster (week 20), and post-booster (week 26). Servings of vegetables and whole grains were evaluated in repeated measures models and results inspected relative to patterns projected from different explanatory models of behavior change processes. Observed changes aligned with projections from the simple associative model of behavior change. Attention in future studies should focus on behavioral intervention elements that leverage stimulus-response associations to increase gratification parents receive from providing their children with healthy lunches.

On a simple cyclic plasticity modeling with implicit kinematic hardening restoration

This paper presents a fully three-dimensional plastic constitutive modeling framework suitable for the prediction of cyclic loading at large number of cycles. It can require only one yield surface and it is motivated by a simple rheological model where a restoration of the kinematic hardening is introduced. The classical kinematic hardening rules are then simply adapted leading to time-dependent evolution laws that are consistent with continuum thermodynamics requirements. The resulting behavior is physically motivated by many man-made materials of engineering interest such as bituminous material. This framework allows all types of yield functions to be easily implemented numerically. This is first illustrated with algorithmic details through a simple associative pressure-insensitive model example of the von Mises type. Then a more elaborated model is given where the present framework is applied to the description of bituminous materials submitted to triaxial static creep and to large number of cyclic loadings. Of particular interest is the ratcheting and the mean stress relaxation. The responses agree well with some experimental test results found in the literature.

Metacognitive monkeys or associative animals? Simple reinforcement learning explains uncertainty in nonhuman animals.

Monkeys will selectively and adaptively learn to avoid the most difficult trials of a perceptual discrimination learning task. Couchman, Coutinho, Beran, and Smith (2010) have recently demonstrated that this pattern of responding does not depend on animals receiving trial-by-trial feedback for their responses; it also obtains if experience of the most difficult trials occurs only under conditions of deferred feedback. Couchman et al. argued that this ruled out accounts based on low-level processes of associative learning and instead required explanation in terms of metacognitive processes of decision monitoring. Contrary to this argument, a simple associative model of reinforcement learning is shown to account for the key findings of Couchman et al.'s empirical study, along with several other findings that have previously been claimed to challenge associative models.

Positional and temporal clustering in serial order memory

The well-known finding that responses in serial recall tend to be clustered around the position of the target item has bolstered positional-coding theories of serial order memory. In the present study, we show that this effect is confounded with another well-known finding--that responses in serial recall tend to also be clustered around the position of the prior recall (temporal clustering). The confound can be alleviated by conditioning each analysis on the positional accuracy of the previously recalled item. The revised analyses show that temporal clustering is much more prevalent in serial recall than is positional clustering. A simple associative chaining model with asymmetric neighboring, remote associations, and a primacy gradient can account for these effects. Using the same parameter values, the model produces reasonable serial position curves and captures the changes in item and order information across study-test trials. In contrast, a prominent positional coding model cannot account for the pattern of clustering uncovered by the new analyses.

What is learned in sequential learning? An associative model of reward magnitude serial-pattern learning.

A computational model of sequence learning is described that is based on pairwise associations and generalization. Simulations by the model predicted that rats should learn a long monotonic pattern of food quantities better than a nonmonotonic pattern, as predicted by rule-learning theory, and that they should learn a short nonmonotonic pattern with highly discriminable elements better than 1 with less discriminable elements, as predicted by interitem association theory. In 2 other studies, the model also simulated behavioral "rule generalization," "extrapolation," and associative transfer data motivated by both rule-learning and associative perspectives. Although these simulations do not rule out the possibility that rats can use rule induction to learn serial patterns, they show that a simple associative model can account for the classical behavioral studies implicating rule learning in reward magnitude serial-pattern learning.

Plausible models of alphabetic search: Reply to Scharroo, Leeuwenberg, Stalmeier, and Vos (1994).

D. Klahr, W. C. Chase, and E. Lovelace (1983) proposed a model of the cognitive processes involved in alphabetic retrieval in terms of a 2-level hierarchy of forward-linked associations. J. Seharroo, E. Leeuwenberg, P. F. M. Stalmeier, and P. G. Vos (1994) attempt to demonstrate that a simple associative model is more plausible, more parsimonious, and a better fit to the data than is Klahr et al.'s model. In this commentary I argue that Seharroo et al. misrepresent the way in which Klahr et al. evaluated their model and that they fail to demonstrate the superiority of a simple associative model. In addition, I suggest that a composite model that integrates the distinctive features of both models would advance our understanding of the process of alphabetic retrieval.

Plausible models of alphabetic search: Reply to Scharroo, Leeuwenberg, Stalmeier, and Vos (1994).

D. Klahr, W. C. Chase, and E. Lovelace (1983) proposed a model of the cognitive processes involved in alphabetic retrieval in terms of a 2-level hierarchy of forward-linked associations. J. Seharroo, E. Leeuwenberg, P. F. M. Stalmeier, and P. G. Vos (1994) attempt to demonstrate that a simple associative model is more plausible, more parsimonious, and a better fit to the data than is Klahr et al.'s model. In this commentary I argue that Seharroo et al. misrepresent the way in which Klahr et al. evaluated their model and that they fail to demonstrate the superiority of a simple associative model. In addition, I suggest that a composite model that integrates the distinctive features of both models would advance our understanding of the process of alphabetic retrieval.

Synthesis, luminescence, and excited-state complexes of the tris(1,10-phenanthroline)- and bis(terpyridine)iridium(III) cations

The authors report the synthesis and luminescence properties of Ir(phen){sub 3}{sup 3+} and Ir(terp){sub 2}{sup 3+} (phen = 1,10-phenanthroline and terp = 2,6-bis(2-pyridyl)pyridine). Their emissions are assigned to predominantly {pi}-{pi}* phosphorescences. A novel excited-state complex is proposed to form between Ir(phen){sub 3}{sup 3+} and Ir(terp){sub 2}{sup 3+} and HgCl{sub 2}. Although HgCl{sub 2} is normally a quencher, it can greatly enhance the lifetimes and luminescence efficiencies of the Ir(phen){sub 3}{sup 3+} and Ir(terp){sub 2}{sup 3+} - up to an order of magnitude. The changes arise from alteration of the radiative and nonradiative rate constants in the excited-state complex. The effect of temperature, solvent, oxygen, and inert ions on the interactions of HgCl{sub 2} with the excited complexes is explored. A simple associative model accurately reproduces all lifetime and intensity changes. A rationale based on the well-known affinity of HgCl{sub 2} for aromatic molecules is proposed.

A physical system approach to recognition memory for spatially transformed faces

Recognition memory for familiar and unfamiliar spatial frequency filtered faces was examined using a combination of experiments and computer simulations based on the physical-systems approach to memory. The results of the experiments showed a significant interaction in recognition performance between the frequency characteristics of the learning and test pictures of the faces. In general, recognition transfer between normal and lowpass faces was good. Transfer between normal and high-pass faces was not as good but improved with the familiarity of the faces. Transfer between high-pass and low-pass faces was poor. A simple linear associative model of the experiment which used only basic visual information about the faces as input produced a pattern of results similar to those seen in the experiments. Memory enhancers aimed at improving the encoding and storage mechanisms of the model produced results similar to those seen when observers were familiar with the faces. These results are discussed in terms of the literature on recognition of faces which have been transformed in different ways and in terms of some psychological interpretations of codes and algorithms used in connectionist models.

The kinetics of hydrogen interaction with TiH x films, 0≤x≲2

The kinetics of hydrogen adsorption on and desorption from TiH x films at room temperature was investigated by quartz crystal microbalance (QCM) measurements. The Ti samples were prepared by evaporation under UHV conditions and exposed to hydrogen at pressures 5 × 10 -8 – 1 × 10 -5 Torr. The absorption kinetics is characterized by three reaction regions. For H/Ti ratios ≲ 0.3 (region I) the sticking coefficient decreases monotonically from an initial sticking coefficient on the clean surface of 0.17. In region II (0.3 ≲ H/Ti ≲ 1.8) the absorption rate is almost constant. When the hydrogen gas is removed, desorption of H 2 is observed and the desorption kinetics is well described by a simple associative desorption model. The desorption rate and the total amount of desorbing H 2 is increasing with increasing pressure during the H 2 exposure, but are relatively insensitive to the H/Ti atom ratio in region II. Only a small fraction of the total hydrogen content in the sample desorbs. A kinetic model is proposed for region II where it is assumed that a surface hydride many atomic layers thick is formed on the sample surface during reaction in region I. The observed desorption is attributed to a decrease in the hydrogen binding energy in the hydride when the H/Ti ratio approaches two. The rate limiting steps in the model are surface adsorption and desorption and diffusion over the surface hydride-bulk interface. In region III the absorption rate decreases and ceases when TiH 2 is formed. Addition of monolayer amounts of CO or O 2 strongly influences the absorption and desorption kinetics. Oxidation of partly hydrided samples virtually passivates the surface against further hydrogen absorption, but addition of small amounts of Ti on top of the oxide results in a recovery of the absorption capability. The oxide obviously strongly reduces the hydrogen dissociation rate but does not act as a diffusion barrier for atomic hydrogen.