Knowledge acquisition for case-based reasoning systems

Case-based reasoning (CBR) is a simple idea: solve new problems by adapting old solutions to similar problems. The CBR approach offers several potential advantages over rule-based reasoning: rules are not combined blindly in a search for solutions, solutions can be explained in terms of concrete examples, and performance can improve automatically as new problems are solved and added to the case library. Moving CBR for the university research environment to the real world requires smooth interfaces for getting knowledge from experts. Described are the basic elements of an interface for acquiring three basic bodies of knowledge that any case-based reasoner requires: the case library of problems and their solutions, the analysis rules that flesh out input problem specifications so that relevant cases can be retrieved, and the adaptation rules that adjust old solutions to fit new problems

Guarantees and Limits of Preprocessing in Constraint Satisfaction and Reasoning

We present a first theoretical analysis of the power of polynomial-time preprocessing for important combinatorial problems from various areas in AI. We consider problems from Constraint Satisfaction, Global Constraints, Satisfiability, Nonmonotonic and Bayesian Reasoning under structural restrictions. All these problems involve two tasks: (i) identifying the structure in the input as required by the restriction, and (ii) using the identified structure to solve the reasoning task efficiently. We show that for most of the considered problems, task (i) admits a polynomial-time preprocessing to a problem kernel whose size is polynomial in a structural problem parameter of the input, in contrast to task (ii) which does not admit such a reduction to a problem kernel of polynomial size, subject to a complexity theoretic assumption. As a notable exception we show that the consistency problem for the AtMost-NValue constraint admits a polynomial kernel consisting of a quadratic number of variables and domain values. Our results provide a firm worst-case guarantees and theoretical boundaries for the performance of polynomial-time preprocessing algorithms for the considered problems.Comment: arXiv admin note: substantial text overlap with arXiv:1104.2541, arXiv:1104.556

Patterns of Clinical Reasoning in Physical Therapist Students

Background and Purpose. Clinical reasoning is a complex, nonlinear problem–solving process that is influenced by models of practice. The development of physical therapists’ clinical reasoning abilities is a crucial yet underresearched aspect of entry-level (professional) physical therapist education. Objectives. The purpose of this qualitative study was to examine the types of clinical reasoning strategies physical therapist students engage in during a patient encounter. Methods. A qualitative descriptive case study design involving within and across case analysis was used. Eight second-year, professional physical therapist students from 2 different programs completed an evaluation and initial intervention for a standardized patient followed by a retrospective think-aloud interview to explicate their reasoning processes. Participants’ clinical reasoning strategies were examined using a 2-stage qualitative method of thematic analysis. Results. Participants demonstrated consistent signs of development of physical therapy–specific reasoning processes, yet varied in their approach to the case and use of reflection. Participants who gave greater attention to patient education and empowerment also demonstrated greater use of reflection-in-action during the patient encounter. One negative case illustrates the variability in the rate at which students may develop these abilities. Conclusions. Participants demonstrated development toward physical therapist–-specific clinical reasoning, yet demonstrated qualitatively different approaches to the patient encounter. Multiple factors, including the use of reflection-in-action, may enable students to develop greater flexibility in their reasoning processes

Reasoning about the Reliability of Diverse Two-Channel Systems in which One Channel is "Possibly Perfect"

This paper considers the problem of reasoning about the reliability of fault-tolerant systems with two "channels" (i.e., components) of which one, A, supports only a claim of reliability, while the other, B, by virtue of extreme simplicity and extensive analysis, supports a plausible claim of "perfection." We begin with the case where either channel can bring the system to a safe state. We show that, conditional upon knowing pA (the probability that A fails on a randomly selected demand) and pB (the probability that channel B is imperfect), a conservative bound on the probability that the system fails on a randomly selected demand is simply pA.pB. That is, there is conditional independence between the events "A fails" and "B is imperfect." The second step of the reasoning involves epistemic uncertainty about (pA, pB) and we show that under quite plausible assumptions, a conservative bound on system pfd can be constructed from point estimates for just three parameters. We discuss the feasibility of establishing credible estimates for these parameters. We extend our analysis from faults of omission to those of commission, and then combine these to yield an analysis for monitored architectures of a kind proposed for aircraft

A Generic Framework for Reasoning about Dynamic Networks of Infinite-State Processes

We propose a framework for reasoning about unbounded dynamic networks of infinite-state processes. We propose Constrained Petri Nets (CPN) as generic models for these networks. They can be seen as Petri nets where tokens (representing occurrences of processes) are colored by values over some potentially infinite data domain such as integers, reals, etc. Furthermore, we define a logic, called CML (colored markings logic), for the description of CPN configurations. CML is a first-order logic over tokens allowing to reason about their locations and their colors. Both CPNs and CML are parametrized by a color logic allowing to express constraints on the colors (data) associated with tokens. We investigate the decidability of the satisfiability problem of CML and its applications in the verification of CPNs. We identify a fragment of CML for which the satisfiability problem is decidable (whenever it is the case for the underlying color logic), and which is closed under the computations of post and pre images for CPNs. These results can be used for several kinds of analysis such as invariance checking, pre-post condition reasoning, and bounded reachability analysis.Comment: 29 pages, 5 tables, 1 figure, extended version of the paper published in the the Proceedings of TACAS 2007, LNCS 442

Effect of Case Presentation on Physical Therapy Students’ Clinical Reasoning

This mixed-methods study investigated the effects of case method presentation on the clinical reasoning hypotheses generated, strategies implemented, and errors made by physical therapy students working through a musculoskeletal clinical problem. The study was framed by Marton and Säljö’s levels of processing, McCrudden’s et al. goal-focusing model, Cognitive Load Theory, and the Model of Domain Learning. Verbatim transcriptions for each problem-solving session was created and coded. Cohen’s kappa was κ = .75 indicating substantial inter-rater reliability for the finalized coding schemes. Quantitative analysis included mean and standard deviation calculations followed by Mann Whitney-U comparisons which detected several significant differences between groups regarding clinical reasoning hypotheses generated, reasoning strategies implemented, and errors made during the problem-solving sessions. Moderate-to-large effect sizes, ranging from r2 = .64–.78, indicated that differences in clinical reasoning between groups was mostly attributed to the case presentation method. Additionally, a qualitative profile enriched the data set by identifying differences in type of knowledge regulation each group exhibited and timing of treatment considerations. Specifically, participants in the simulated patient group were found to regulate more psychomotor skill knowledge compared to the written case study group who exhibited more regulation of propositional knowledge. This research project has already impacted the educational experiences physical therapy students receive in their professional education program. Future research should include multi-institutional investigations with a larger number of participants allowing for better representation of physical therapy students across professional education programs before generalizing any findings

The VEX-93 environment as a hybrid tool for developing knowledge systems with different problem solving techniques

The paper describes VEX-93 as a hybrid environment for developing knowledge-based and problem solver systems. It integrates methods and techniques from artificial intelligence, image and signal processing and data analysis, which can be mixed. Two hierarchical levels of reasoning contains an intelligent toolbox with one upper strategic inference engine and four lower ones containing specific reasoning models: truth-functional (rule-based), probabilistic (causal networks), fuzzy (rule-based) and case-based (frames). There are image/signal processing-analysis capabilities in the form of programming languages with more than one hundred primitive functions. User-made programs are embeddable within knowledge basis, allowing the combination of perception and reasoning. The data analyzer toolbox contains a collection of numerical classification, pattern recognition and ordination methods, with neural network tools and a data base query language at inference engines's disposal. VEX-93 is an open system able to communicate with external computer programs relevant to a particular application. Metaknowledge can be used for elaborate conclusions, and man-machine interaction includes, besides windows and graphical interfaces, acceptance of voice commands and production of speech output. The system was conceived for real-world applications in general domains, but an example of a concrete medical diagnostic support system at present under completion as a cuban-spanish project is mentioned. Present version of VEX-93 is a huge system composed by about one and half millions of lines of C code and runs in microcomputers under Windows 3.1.Postprint (published version

THE LIVING CASE: SEARCHING FOR A DEEPER STRUCTURE IN THE CASE ANALYSIS PROCESS

One of the primary methods of instruction in business disciplines is the case. However, in its current form of written presentation, some of the basic learning goals associated with case instruction are compromised. We have used new forms of media involving computing and communication to build a novel learning environment, the Living Case, which flexibly and interactively presents cases along with provide dynamic, on-going feedback to students analyzing a case. In our research we have formalized the process of analyzing a case in order to recognize and interpret student analysis behavior so that provide relevant assistance can be provided. Case analysis is characterized as a problem solving activity driven by comprehension and reasoning operators. A search for these operators led us to build an inventory of reading activities. Twelve hours of protocols are analyzed using "retelling profiles" as an interpretation mechanism. Retelling profiles are visual time plots of the activities undertaken in a reading task. Our preliminary results suggest a deeper structure to case analysis which is common across business disciplines, cases, and individuals. Differences between the analysis strategies of experts and novices are also formalized. Finally, an expert's analogical reasoning strategy using task-specific knowledge encoded as "templates" is identified as a major contributor to their efficiency in solving cases. Templates of typical company situations and responses are triggered early in the analysis process, and subsequent data gathering and reasoning is directed by an attempt to apply the template to the case situation.Information Systems Working Papers Serie

Kemampuan Literasi Matematis Siswa Ditinjau dari Kemampuan Pemecahan Masalah Siswa SMP di Pontianak

This research aims to describe student's mathmatical literacy ability in terms of problem solving skill in Junior High School Pontianak. This research used descriptive method with case study research design. Subject of this research design were 6 students of grade VIII E with different problem solving skill based on problems' contextuality level as been stated by Jan De Lange. The literacy aspects which were discussed in this research included reasoning and communication aspects. The data analysis showed student who satisfied the criterias of reasoning aspect were actually student in high level problem solving skill. Reciprocally, students who satisfied the criterias of communication aspect were also students with high level of problem solving skill. But generally, students' mathematical literacy ability in terms of problem solving skill was classified as low category