Competing Models of Analogy: ACME Versus Copycat

ACME and Copycat have been viewed as competing models of analogy making. Mitchell (1993) makes three major criticisms of ACM E in arguing for Copycat's superiority: that because ACME considers all syntactically possible mappings it is psychologically implausible and computationally infeasible; that its representations are rigid and hand-tailored for each problem; and that ACME's representations are scmantically empty. To evaluate these criticisms we applied ACME to simulating problems in the only domain addressed by Copycat, letter-string analogies such as, "If abc is changed into abd, how would you change kji in the same way?" Using representations that include only knowledge available to Copycat, ACME generated the most common solutions that people and Copycat produce. In addition, ACME was able to generate some solutions produced by people but that are impossible for Copycat, demonstrating that in some respects ACME is a more flexible analogical reasoner than is Copycat. These simulations answer each of Mitchell's criticisms of ACME . ACME can incorporate domain-relevant knowledge to allow a principled reduction in the number of mappings considered; it can generate novel representations based on its domain-general constraints; and it can incorporate semantic content into its representations. In addition, ACME has the advantage of being applicable to many different domains

Headwaters are critical reservoirs of microbial diversity for fluvial networks

Streams and rivers form conspicuous networks on the Earth and are among nature's most effective integrators. Their dendritic structure reaches into the terrestrial landscape and accumulates water and sediment en route from abundant headwater streams to a single river mouth. The prevailing view over the last decades has been that biological diversity also accumulates downstream. Here, we show that this pattern does not hold for fluvial biofilms, which are the dominant mode of microbial life in streams and rivers and which fulfil critical ecosystem functions therein. Using 454 pyrosequencing on benthic biofilms from 114 streams, we found that microbial diversity decreased from headwaters downstream and especially at confluences. We suggest that the local environment and biotic interactions may modify the influence of metacommunity connectivity on local biofilm biodiversity throughout the network. In addition, there was a high degree of variability in species composition among headwater streams that could not be explained by geographical distance between catchments. This suggests that the dendritic nature of fluvial networks constrains the distributional patterns of microbial diversity similar to that of animals. Our observations highlight the contributions that headwaters make in the maintenance of microbial biodiversity in fluvial networks

Goal Speciflcity in Hypothesis Testing and Problem Solving

Theories of skill acquisition have made radically different predictions about the role of means-ends analysis in acquiring general rules that promote effective transfer to new problems. Under one view, means-ends analysis is assumed to provide the basis for efficient knowledge compilation (Anderson, 1987), whereas under the alternative view means-ends analysis is believed to disrupt rule induction (Sweller, 1988). We suggest that in the absence of a specific goal people are more likely to use a rule-induction learning strategy, whereas providing a speciflc goal fosters use of means ends analysis, which is a non-rule-induction strategy. We performed an experiment to investigate the impact of goal specificity and systematicity of rule-induction strategies in learning and transfer within a complex dynamic system. Subjects who were provided with a specific goal were able to solve the initial problem, but were impaired on a transfer test using a similar problem with a different goal, relative to subjects who were encouraged to use a systematic rule-induction strategy to freely explore the problem space. Our results support Sweller's proposal that means-ends analysis leads to specific knowledge of an isolated solution path, but docs not provide an effective method for learning the overall structure of a problem space

Advancing With Age: Older Adults Excel in Comprehension of Novel Metaphors

Older adults may experience certain forms of cognitive decline, but some forms of semantic memory remain intact in older age. To address how metaphor comprehension changes with age and whether metaphor comprehension relies more heavily on analogical reasoning (supported by fluid intelligence) or on conceptual combination (supported by crystalized intelligence), we compared performance of younger and older adults. In two experiments, healthy older adults (54-88 years) scored lower on a measure of fluid intelligence (Ravens Progressive Matrices) but higher on a measure of crystalized intelligence (Mill Hill Vocabulary Test) relative to younger adults (18-34 years). Groups were equally successful in comprehending relatively easy metaphors (Study 1), but older adults showed a striking advantage over younger adults for novel literary metaphors (Study 2). Mixed-effects modeling showed that measures of fluid and crystalized intelligence each made separable contributions to metaphor comprehension for both groups, but older adults relied more on crystalized intelligence than did younger adults. These age-related dissociations clarify cognitive effects of aging and highlight the importance of crystalized intelligence for metaphor comprehension in both younger and older adults. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

International entrepreneurship : exploring the logic and utility of individual experience through comparative reasoning approaches

In this paper, we suggest that individual experience and reasoning, as applied to new endeavors in internationalization, are concepts with high potential to advance conceptual and empirical research in international entrepreneurship (IE). Experience is known to be important in internationalization, but the logic or reasoning with which it is applied is insufficiently understood. Cognitive, comparison-based reasoning theories explain how individuals draw on experience to make sense of uncertain, novel, and complex situations. Drawing on two such theories, heuristics and analogical reasoning, we delineate the logic of experience and advance speculative propositions on its utility in the context of internationalization research

Structural mapping in statistical word problems: A relational reasoning approach to Bayesian inference

Presenting natural frequencies facilitates Bayesian inferences relative to using percentages. Nevertheless, many people, including highly educated and skilled reasoners, still fail to provide Bayesian responses to these computationally simple problems. We show that the complexity of relational reasoning (e.g., the structural mapping between the presented and requested relations) can help explain the remaining difficulties. With a non-Bayesian inference that required identical arithmetic but afforded a more direct structural mapping, performance was universally high. Furthermore, reducing the relational demands of the task through questions that directed reasoners to use the presented statistics, as compared with questions that prompted the representation of a second, similar sample, also significantly improved reasoning. Distinct error patterns were also observed between these presented- and similar-sample scenarios, which suggested differences in relational-reasoning strategies. On the other hand, while higher numeracy was associated with better Bayesian reasoning, higher-numerate reasoners were not immune to the relational complexity of the task. Together, these findings validate the relational-reasoning view of Bayesian problem solving and highlight the importance of considering not only the presented task structure, but also the complexity of the structural alignment between the presented and requested relations

Ecological equivalence: a realistic assumption for niche theory as a testable alternative to neutral theory

Hubbell's 2001 neutral theory unifies biodiversity and biogeography by modelling steady-state distributions of species richness and abundances across spatio-temporal scales. Accurate predictions have issued from its core premise that all species have identical vital rates. Yet no ecologist believes that species are identical in reality. Here I explain this paradox in terms of the ecological equivalence that species must achieve at their coexistence equilibrium, defined by zero net fitness for all regardless of intrinsic differences between them. I show that the distinction of realised from intrinsic vital rates is crucial to evaluating community resilience. An analysis of competitive interactions reveals how zero-sum patterns of abundance emerge for species with contrasting life-history traits as for identical species. I develop a stochastic model to simulate community assembly from a random drift of invasions sustaining the dynamics of recruitment following deaths and extinctions. Species are allocated identical intrinsic vital rates for neutral dynamics, or random intrinsic vital rates and competitive abilities for niche dynamics either on a continuous scale or between dominant-fugitive extremes. Resulting communities have steady-state distributions of the same type for more or less extremely differentiated species as for identical species. All produce negatively skewed log-normal distributions of species abundance, zero-sum relationships of total abundance to area, and Arrhenius relationships of species to area. Intrinsically identical species nevertheless support fewer total individuals, because their densities impact as strongly on each other as on themselves. Truly neutral communities have measurably lower abundance/area and higher species/abundance ratios. Neutral scenarios can be parameterized as null hypotheses for testing competitive release, which is a sure signal of niche dynamics. Ignoring the true strength of interactions between and within species risks a substantial misrepresentation of community resilience to habitat los

Computational and Biological Analogies for Understanding Fine-Tuned Parameters in Physics

In this philosophical paper, we explore computational and biological analogies to address the fine-tuning problem in cosmology. We first clarify what it means for physical constants or initial conditions to be fine-tuned. We review important distinctions such as the dimensionless and dimensional physical constants, and the classification of constants proposed by Levy-Leblond. Then we explore how two great analogies, computational and biological, can give new insights into our problem. This paper includes a preliminary study to examine the two analogies. Importantly, analogies are both useful and fundamental cognitive tools, but can also be misused or misinterpreted. The idea that our universe might be modelled as a computational entity is analysed, and we discuss the distinction between physical laws and initial conditions using algorithmic information theory. Smolin introduced the theory of "Cosmological Natural Selection" with a biological analogy in mind. We examine an extension of this analogy involving intelligent life. We discuss if and how this extension could be legitimated. Keywords: origin of the universe, fine-tuning, physical constants, initial conditions, computational universe, biological universe, role of intelligent life, cosmological natural selection, cosmological artificial selection, artificial cosmogenesis.Comment: 25 pages, Foundations of Science, in pres

Identifying the mechanisms underpinning recognition of structured sequences of action

© 2012 The Experimental Psychology SocietyWe present three experiments to identify the specific information sources that skilled participants use to make recognition judgements when presented with dynamic, structured stimuli. A group of less skilled participants acted as controls. In all experiments, participants were presented with filmed stimuli containing structured action sequences. In a subsequent recognition phase, participants were presented with new and previously seen stimuli and were required to make judgements as to whether or not each sequence had been presented earlier (or were edited versions of earlier sequences). In Experiment 1, skilled participants demonstrated superior sensitivity in recognition when viewing dynamic clips compared with static images and clips where the frames were presented in a nonsequential, randomized manner, implicating the importance of motion information when identifying familiar or unfamiliar sequences. In Experiment 2, we presented normal and mirror-reversed sequences in order to distort access to absolute motion information. Skilled participants demonstrated superior recognition sensitivity, but no significant differences were observed across viewing conditions, leading to the suggestion that skilled participants are more likely to extract relative rather than absolute motion when making such judgements. In Experiment 3, we manipulated relative motion information by occluding several display features for the duration of each film sequence. A significant decrement in performance was reported when centrally located features were occluded compared to those located in more peripheral positions. Findings indicate that skilled participants are particularly sensitive to relative motion information when attempting to identify familiarity in dynamic, visual displays involving interaction between numerous features