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The acquisition of relational concepts plays an integral role and is assumed to be a prerequisite for analogical reasoning. Language and token-trained apes (e.g. Premack, 1976; Thompson, Oden, and Boysen, 1997) are the only nonhuman animals to succeed in solving and completing analogies, thus implicating language as the mechanism enabling the phenomenon. In the present study, I examine the role of meaning in the analogical reasoning abilities of three different primate species. Humans, chimpanzees, and rhesus monkeys completed relational match-to-sample (RMTS) tasks with either meaningful or nonmeaningful stimuli. For human participants, meaningfulness facilitated the acquisition of analogical rules. Individual differences were evident amongst the chimpanzees suggesting that meaning can either enable or hinder their ability to complete analogies. Rhesus monkeys did not succeed in either condition, suggesting that their ability to reason analogically, if present at all, may be dependent upon a dimension other than the representational value of stimuli.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: Analogy, Design, Functional Modeling, Functional Reasoning, Knowledge Representation, Repertory Grid, SME, Structure Mapping Engine, AI in design. Includes bibliographical references (p.106).

Ever since artifacts have been produced, improving them has been a common human activity. Improving an artifact refers to modifying it such that it will be either easier to produce, or easier to use, or easier to fix, or easier to maintain, and so on. In all of these cases, "easier" means fewer resources are required for those processes. While 'resources' is a general measure, which can ultimately be expressed by some measure of cost (such as time or money), we believe that at the core of many improvements is the notion of reduction of complexity, or in other words, simplification. This talk presents our research on performing design simplification using analogical reasoning. We first define the simplification problem as the problem of reducing the complexity of an artefact from a given point of view. We propose that a point of view from which the complexity of an artefact can be measured consists of a context, an aspect and a measure. Next, we describe an approach to solving simplification problems by goal-directed analogical reasoning, as our implementation of this approach. Finally, we present some experimental results obtained with the system. The research presented in this dissertation is significant as it focuses on the intersection of a number of important, active research areas - analogical reasoning, functional representation, functional reasoning, simplification, and the general area of AI in Design.

It is well documented that undergraduate students struggle with the more formal and abstract concepts of vector space theory in a first course on linear algebra. Some of these students continue on to classes in abstract algebra, where they learn about algebraic structures such as groups. It is clear to the seasoned mathematician that vector spaces are in fact groups, and so linear transformations are group homomorphisms with extra restrictions. This study explores the question of whether or not students see this connection as well. In addition, I probe the ways in which students’ stated understandings are the same or different across contexts, and how these differences may help or hinder connection making across domains. Students’ understandings are also briefly compared to those of mathematics professors in order to highlight similarities and discrepancies between reality and idealistic expectations. The data for this study primarily comes from clinical interviews with ten undergraduates and three professors. The clinical interviews contained multiple card sorts in which students expressed the connections they saw within and across the domains of linear algebra and abstract algebra, with an emphasis specifically on linear transformations and group homomorphisms. Qualitative data was analyzed using abductive reasoning through multiple rounds of coding and generating themes. Overall, I found that students ranged from having very few connections, to beginning to form connections once placed in the interview setting, to already having a well-integrated morphism schema across domains. A considerable portion of this paper explores the many and varied ways in which students succeeded and failed in making mathematically correct connections, using the language of research on analogical reasoning to frame the discussion. Of particular interest were the ways in which isomorphisms did or did not play a role in understanding both morphisms, how students did not regularly connect the concepts of matrices and linear transformations, and how vector spaces were not fully aligned with groups as algebraic structures.

A well-researched line showing equivalence performances in a wide variety of areas has been conducted in the field of Behavior Analysis (BA). One area demonstrates that relating relations is a behavioral account of analogical thinking. Relating relations may have implications for the development of analogical training given that analogical reasoning is seen as the foundation of intelligence yet research in this area is limited. A protocol by Stewart, Barnes-Holmes, and Weil (2009) was developed to train children in analogical reasoning using equivalence-equivalence relations. The purpose of this study was to evaluate an equivalence-equivalence training protocol based on Stewart et al. (2009) and test whether the protocol was effective in training equivalence-equivalence responding to 7 and 8-year-old children. A secondary purpose was to test whether training in equivalence-equivalence responding increased performances on analogical tests. All five participants were dismissed throughout the study. Participant 1 was dismissed during the pre-assessments and all other participants were dismissed during intervention. Because none of the participants passed the equivalence-equivalence training, increases in performance in analogical testes were not analyzed. Individual performance data from training are examined and analyzed to provide an account of the failures to pass the equivalence-equivalence protocol.

Model integration that allows multiple models to work together for solving a sophisticated problem has been an important research issue in the management of decision models. The recent development of the service-oriented architecture (SOA) has provided an opportunity to apply this new technology to support model integration. This is particularly critical when more and more models are delivered as web services. A web-services-based approach to model management is useful in providing effective decision support. In the past, existing literature has adopted the approach that treated a model as a service. Model integration can be thought of as a composition of web services. In the composition process, proper components and their relationships must be properly identified. This requires accurate model definition and reasoning. In the research, we propose a semantic-based approach for developing such as system. The approach uses DAML-S to describe the capability of a service. Then the system can discover proper services for a particular requirement by using semantic matching on these DAML-S documents. When suitable web services are found, the system uses BPEL4WS to composite them together. The resulting composite web service can be applied to decision support. A prototype that demonstrates the feasibility of the proposed approach is implemented in Java.

The acquisition of relational concepts plays an integral role and is assumed to be a prerequisite for analogical reasoning. Language and token-trained apes (e.g. Premack, 1976; Thompson, Oden, and Boysen, 1997) are the only nonhuman animals to succeed in solving and completing analogies, thus implicating language as the mechanism enabling the phenomenon. In the present study, I examine the role of meaning in the analogical reasoning abilities of three different primate species. Humans, chimpanzees, and rhesus monkeys completed relational match-to-sample (RMTS) tasks with either meaningful or nonmeaningful stimuli. For human participants, meaningfulness facilitated the acquisition of analogical rules. Individual differences were evident amongst the chimpanzees suggesting that meaning can either enable or hinder their ability to complete analogies. Rhesus monkeys did not succeed in either condition, suggesting that their ability to reason analogically, if present at all, may be dependent upon a dimension other than the representational value of stimuli.

In recent years, the field of design has met new grounds with the growing awareness among design researchers of the potential relationships between cognitive studies of creativity and computational modeling. The turn of the studies has given rise to the emergence of a new paradigm of modeling and understanding mental processes in creative design. This study tries to gain further insight into the creative occurrence by blending virtual experiences with designer actions in a model of creative thinking in concept generation phase based on the Geneplore Model by Finke et al. (1995) and supported by analogy construction incorporating the implementation of a computer based tool (Black Box) running on PC platform as a potential immanent part of the concept generation phase. Black Box is devised in such a way that the core of the constructive process of the analogy relies on the designer&amp / #8217 / s expressional, perceptual and conceptual actions which are presented in the traditional methods of sketching and writing, whereas the change and expansion of the design space is realized through the virtual worlds the tool offers via the computer screen. The research method is based on the development of Black Box tool and its subsequent implementation in a study with eight experienced design consultants, utilizing a procedure composed of preliminary interview, observational protocol analysis, questionnaire and retrospective interview. Through encoding actions of individual designers by means of their maps in the computational tool, the study yields significant results in revealing differing thinking maps of different designers which have been used to propose a general creative thinking map of concept generation in Black Box presented in a way to be adapted for further studies. Moreover, the study provided insight on the methods used to assist creativity in concept generation by different designers, on the selection of inspirational material and on the integration of analogies as knowledge transformers to evoke design concepts.

The recent development of the service-oriented architecture (SOA) has provided an opportunity to apply this new technology to support model management. This is particularly critical when more and more decision models are delivered as web services. A web-services-based approach to model management is useful in providing effective decision support. When a decision model is implemented as a web service, it is called a model-based web service. In model management, selecting a proper model-based web service is an important issue. Most current research on selecting such web service relies on matching inputs and outputs of the model, which is oversimplified. The incorporation of more semantic knowledge may be necessary to make the selection of model-based web services more effective. In this research, we propose a new mechanism that represents the semantics associated with a problem and then use the similarity of semantic information between a new problem description and existing web services to find the most suitable web services for solving the new problem. The paper defines the concept of entity similarity, attribute similarity, and functional similarity for problem matching. The web service that has the highest similarity is chosen as a base for constructing the new web services. The identified mapping is converted into BPEL4WS codes for utilizing the web services. To verify the feasibility of the proposed method, a prototype system has been implemented in JAVA.