By introducing and extending description logic (DLs) and growing up their application in knowledge representation and especially in OWLs and semantic web scope, many shortcomings and bugs were identified that weren’t resolvable in classical DLs and so logicians and computer scientists intended to non-classical and non-monotonic reasoning tools. In this paper, I discuses about abduction problem solvers, and by introducing A-Box abduction in description logics (DLs), such as ALC, discuss about decidability and complexity in different introduced algorithms, (...) and report shortly our team’s advantages in developing and implementation of ΑBox abduction in DLs. (shrink)

This essay begins by dividing the traditional problem of free will and determinism into a “correlation” problem and an “explanation” problem. I then focus on the explanation problem, and argue that a standard form of abductive (i.e. inference to the best-explanation) reasoning may be useful in solving it. To demonstrate the fruitfulness of the abductive approach, I apply it to three standard accounts of free will. While each account implies the same solution to the correlation (...) problem, each implies a unique solution to the explanation problem. For example, all libertarian-friendly accounts of free will imply that it is impossible to act freely when determinism is true. However, only a narrow subset of libertarians have the theoretical resources to defend the incompatibilist claim that deterministic laws (qua being deterministic) undermine free will, while other libertarians must reject this incompatibilist view. -/- [Version: Nov. 12, 2018]. (shrink)

The aim of this paper is to investigate the relationship between information and abductive reasoning in the context of problem-solving, focusing on non-human animals. Two questions guide our investigation: What is the relation between information and abductive reasoning in the context of human and non-human animals? Do non-human animals perform discovery based on inferential processes such as abductive reasoning? In order to answer these questions, we discuss the semiotic concept of information in relation to the concept of abductive (...) reasoning and, more specifically, to the notion of manipulative abduction proposed by Magnani. Finally, we investigate a case study of corvids’ intelligence, namely, their capacity of causal cognition. (shrink)

We describe a general problem solving mechanism that is especially suited for performing a particular form of abductive inference, or best-explanation finding. A problem solver embodying this mechanism synthesizes composite hypotheses. It does so by by combining hypothesis parts as a means to the satisfaction of explanatory goals. In this way it is able to arrive at complex, integrated conclusions which are not pre-stored.The intent is to present a computationally-feasible, task-specific problem solver for a particular information (...) processing task which is nevertheless of very great generality. The task is that of synthesizing coherent composite explanatory hypotheses based upon a prestored, and possibly vast collection of hypothesis-generating “concepts”. The authors’ claim is nothing less than to have shown, in a new sense, and surpassing all other work in this area, how it is computationally possible for an agent to come to “know”, based upon the evidence of the case. (shrink)

Red-2 is a computer program for red-cell antibody identification, a piece of "normal science". Abstracting from Red-2, a general problem solving mechanism is described that is especially suited for performing a form of abductive inference or best explanation finding. A problem solver embodying this mechanism synthesizes composite hypotheses by combining hypothesis parts. This is a common task of intelligence, and a component of scientific reasoning. The work addresses the question, 'How is science possible?' by showing how a (...) simple but powerful form of hypothesis synthesis is computationally feasible. (shrink)

CS Peirce introduced the concept of abduction into our epistemic lexicon. It is a view of problem solving that emphasizes ecological contexts, preparatory or predictive predilection knotted to learning and inquiry. Abduction is essentially tied more broadly to pragmatism. One view of the brain reflects the fact that predictive predilections knotted to abduction or hypothesis testing dominates the landscape of diverse forms of problem solving. Abduction is biologically constrained and contextual, not a (...) monolithic term and runs the range of neural capability. (shrink)

A constantly changing social reality means economic theories, even if correct today, need to be constantly revised, updated, or abandoned. To maintain an up-to-date understanding of its subject matter, economists have to continuously assess their theories even those that appear to be empirically corroborated. Economics could gain from a method that describes and is capable of generating novel explanatory hypotheses. A pessimistic view on the existence of such a method was famously articulated by Karl Popper in The Logic of Scientific (...) Discovery. He wrote ‘there is no such a thing as a logical method of having ideas or a logical reconstruction of this process.’ Herbert Simon responded to Popper and argued the opposite, namely, that there is a model of discovery and its name is abduction. Simon acknowledges his debt to Charles Peirce – the first modern logician to explicitly formulate a theory of abduction – and explains that abduction is a model of discovery that works as a problem-solving heuristic encoded.. (shrink)

“Selective abduction” is a notion coined by L. Magnani, who contrasts it with the more common notion of “creative abduction”. However, selective abduction may easily be confused with inference to the best explanation. This constitutes a problem, if IBE is reconstructed as an inductive inference. For on the one hand, abduction and induction must be distinct. On the other hand, Gabbay and Woods, but also Hintikka and Kapitan, even include hypothesis selection as part and parcel (...) of the abductive inference per se. Consequently, there seems to be a riddle about what selective abduction clearly means and how it could be distinguished from other forms of reasoning. The contribution tries to solve this problem by explicating selective abduction and embedding it in an overall taxonomy of inferences. (shrink)

This paper introduces an epistemological model of scientific reasoning which can be described in terms of abduction, deduction and induction. The aim is to emphasize the significance of abduction in order to illustrate the problem-solving process and to propose a unified epistemological model of scientific discovery. The model first describes the different meanings of the word abduction in order to clarify their significance for epistemology and artificial intelligence. In different theoretical changes in theoretical systems we (...) witness different kinds of discovery processes operating. Discovery methods are "data-driven," "explanation-driven", and "coherence-driven". Sometimes there is a mixture of such methods: for example, an hypothesis devoted to overcome a contradiction is found by abduction. Contradiction, far from damaging a system, help to indicate regions in which it can be changed and improved. I will also consider a kind of "weak" hypothesis that is hard to negate and the ways for making it easy. In these cases the subject can "rationally" decide to withdraw his or her hypotheses even in contexts where it is "impossible" to find "explicit" contradictions and anomalies. Here, the use of negation as failure is illuminating. (shrink)

The purpose of this study was to investigate the features of modeling-based abductive reasoning as a disciplinary practice of inquiry in the domain of earth science. The study was based on an undergraduate course of a university of education, Korea, offered for preservice elementary teachers majoring in science as their specialty. The course enrollees participated in an inquiry project in which they were asked to abductively generate models representing past geologic events in order to explain how two units in a (...) sedimentary rock outcrop had been formed. Three students were selected as major informants for the study, and multiple types of qualitative data were collected, including the students’ sketchbook records, audio-recording of whole-class presentation and discussion, and interviews with the students. The data were analyzed according to the method of analytical induction, which yielded three assertions as the findings of the study. First, while an explanatory model can be generated by combining resource models, the combination of resource models does not necessarily result in a scientifically sound explanatory model. Second, a systemic approach can help activate a critical resource model which can in turn lead to a scientifically sound explanatory model. Third, simulations with a model can enhance the plausibility of the model. Based on these findings, causal combinations of resource models, a systemic approach to earth scientific problem-solving, and simulations with a model are suggested and discussed as implications for science education and relevant research. (shrink)

In this paper, we present a goal-directed proof procedure for abductive reasoning. This procedure will be compared with Aliseda’s approach based on semantic tableaux. We begin with some comments on Aliseda’s algorithms for computing conjunctive abductions and show that they do not entirely live up to their aims. Next we give a concise account of goal-directed proofs and we show that abductive explanations are a natural spin-off of these proofs. Finally, we show that the goal-directed procedure solves the problems we (...) encountered in Aliseda’s algorithms. (shrink)

In this paper, we present a goal-directed proof procedure for abductive reasoning. This procedure will be compared with Aliseda’s approach based on semantic tableaux. We begin with some comments on Aliseda’s algorithms for computing conjunctive abductions and show that they do not entirely live up to their aims. Next we give a concise account of goal-directed proofs and we show that abductive explanations are a natural spin-off of these proofs. Finally, we show that the goal-directed procedure solves the problems we (...) encountered in Aliseda’s algorithms. (shrink)

More than a hundred years ago, the American philosopher C. S. Peirce suggested the idea of pragmatism as a logical criterion to analyze what words and concepts express through their practical meaning. Many words have been spent on creative processes and reasoning, especially in the case of scientific practices. In fact, philosophers have usually offered a number of ways of construing hypotheses generation, but all aim at demonstrating that the activity of generating hypotheses is paradoxical, illusory or obscure, and thus (...) not analyzable. The “computational turn” gave us a new way to understand creative processes in a strictly pragmatic sense. Artificial Intelligence and Cognitive Science tools allow us to test concepts and ideas previously conceived in abstract terms. It is in the perspective of these actual models that we find the central role of abduction in the explanation of creative reasoning in science. What I call theoretical abduction certainly illustrates much of what is important in abductive reasoning, especially the objective of selecting and creating a set of hypotheses that are able to dispense good explanations of data, but fails to account for many cases of explanation occurring in science or in everyday reasoning when the exploitation of the environment is crucial. The concept of manipulative abduction is devoted to capture the role of action in many interesting situations: action provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. Many external things, usually inert from the epistemological point of view, can be transformed into what I call epistemic mediators, which are illustrated in the last part of the paper. (shrink)

In multicausal abductive tasks a person must explain some findings by assembling a composite hypothesis that consists of one or more elementary hypotheses. If there are n elementary hypotheses, there can be up to 2n composite hypotheses. To constrain the search for hypotheses to explain a new observation, people sometimes use their current explanation—the previous evidence and their present composite hypothesis of that evidence; however, it is unclear when and how the current explanation is used. In addition, although a person's (...) current explanation can narrow the search for a hypothesis, it can also blind the problem solver to alternative, possibly better, explanations. This paper describes a model of multicausal abductive reasoning that makes two predictions regarding the use of the current explanation. The first prediction is that the current explanation is not used to explain new evidence if there is a simple (i.e., nondisjunctive, concrete) hypothesis to account for that evidence. The second prediction is that the current explanation is used when attempting to discriminate among several alternative hypotheses for new evidence. These hypotheses were tested in three experiments. The results are consistent with the second prediction: the current explanation is used when discriminating among alternative hypotheses. However, the first prediction—that the current explanation is not used when a simple hypothesis can account for new data—received only limited support. Participants used the current explanation to constrain their interpretation of new data in 46.5% of all trials. This suggests that context‐independent strategies compete with context‐dependent ones—an interpretation that is consistent with recent work on strategy selection during problem solving. (shrink)

This paper argues that Umberto Eco had a sophisticated theory of abductive reasoning and that this theory is fundamentally akin to Peirce’s both in the analysis and in the justification of this kind of reasoning. The first section expounds the essentials of Peirce’s theory of abduction, and explains how Peirce moved from seeing abduction as a kind of reasoning to seeing it as a stage of the larger process of inquiry. The second section deals with one of Eco’s (...) paradigmatic examples of abduction, i.e., William of Baskerville’s abduction concerning the horse Brunellus in the overture of The Name of the Rose, and shows that, just like in Peirce’s three-stages model of inquiry, William’s abductions are verified by means of deduction and induction. The third section examines the problem of the justification of abductive reasoning, and argues that both Peirce and Eco solved this problem through the idea that the justification of abduction is itself abductive (meta-abduction in Eco, ur-abduction in Peirce). (shrink)

What I call theoretical abduction (sentential and model-based)certainly illustrates much of what is important in abductive reasoning, especially the objective of selecting and creating a set of hypotheses that are able to dispense good (preferred) explanations of data, but fails to account for many cases of explanation occurring in science or in everyday reasoning when the exploitation of the environment is crucial. The concept of manipulative abduction is devoted to capture the role of action in many interesting situations: (...) action provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. Many external things, usually inert from the epistemological point of view, can be transformed into what I call epistemic mediators, which are illustrated in the last part of the paper, together with an analysis of the related notions of ``perceptual and inceptual rehearsal'' and of ``external representation''. (shrink)

This study aims to understand scientific inference for the evolutionary procedure of Continental Drift based on abductive inference, which is important for creative inference and scientific discovery during problem solving. We present the following two research problems: (1) we suggest a scientific inference procedure as well as various strategies and a criterion for choosing hypotheses over other competing or previous hypotheses; aspects of this procedure include puzzling observation, abduction, retroduction, updating, deduction, induction, and recycle; and (2) we (...) analyze the “theory of continental drift” discovery, called the Earth science revolution, using our multistage inference procedure. Wegener’s Continental Drift hypothesis had an impact comparable to the revolution caused by Darwin’s theory of evolution in biology. Finally, the suggested inquiry inference model can provide us with a more consistent view of science and promote a deeper understanding of scientific concepts. (shrink)

Many parts of the contemporary philosophical debate have been built on the radicalization of conclusions derived from the acceptance of a certain set of classical dichotomies. It also discusses how pragmatism and abduction are currently presented to solve the problems arising from these dichotomies. For this reason, the efforts of this article have been directed to analyze the impact of this fact on the philosophy of science and logic. The starting point is that accepting abduction implies, in many (...) ways, accepting the foundations of pragmatism. Also, that the analysis of such problems from pragmatism and the particular use of abduction dissolve the dichotomies and, with it, also modify the philosophical problems related to them. Therefore, I propose to understand abduction as the right conceptual device to review the problems and debates of the twentieth century’s epistemology from a pragmatic perspective. In doing so, the aim is to propose that the current use of abduction in contemporary debates may imply a change of the philosophical perspective. (shrink)

In criminal cases at common law, juries are permitted to convict on wholly circumstantial evidence even in the face of a reasonable case for acquittal. This generates the highly counterintuitive—if not absurd—consequence that there being reason to think that the accused didn’t do it is not reason to doubt that he did. This is the no-reason-to-doubt problem. It has a technical solution provided that the evidence on which it is reasonable to think that the accused didn’t do it is (...) a different subset of the total evidence from that on which there is no reason to doubt that he did do it. It lies in the adversarial nature of criminal proceedings in the common law tradition that the subsets of the total evidence on which counsel base their opposing arguments are themselves different from and often incompatible with one another. While this solves the no-reason-to-doubt problem, it does so at the cost of triggering a second problem just as bad. It is the no-rival problem, according to which incompatible theories of the case based on incompatible subsets of the evidence cannot be rivals of one another. If neither party’s case contradicts the other’s then, by the burden of proof requirement, criminal convictions are impossible. Once having generated the dilemma, the object of the paper is to determine how it might be escaped. (shrink)

This paper formulates what I think is the basic problem of any attempt to characterise the abstract structure of scientific method, viz., that it has to satisfy two conflicting desiderata: it should be ampliative (contentincreasing) and it should confer epistemic warrant on its outcomes. Then, after two extreme solutions to the problem of the method, viz., Enumerative Induction and the Method of Hypothesis, are examined, the paper argues that abduction, suitably understood as Inference to the Best Explanation, (...) offers the best description of scientific method and solves the foregoing problem in the best way: it strikes the best balance between ampliation and epistemic warrant. (shrink)

In the course of daily life we solve problems often enough that there is a special term to characterize the activity and the right to expect a scientific theory to explain its dynamics. The classical view in psychology is that to solve a problem a subject must frame it by creating an internal representation of the problem’s structure, usually called a problem space. This space is an internally generable representation that is mathematically identical to a graph structure (...) with nodes and links. The nodes can be annotated with useful information, and the whole representation can be distributed over internal and external structures such as symbolic notations on paper or diagrams. If the representation is distributed across internal and external structures the subject must be able to keep track of activity in the distributed structure. Problem solving proceeds as the subject works from an initial state in mentally supported space, actively constructing possible solution paths, evaluating them and heuristically choosing the best. Control of this exploratory process is not well understood, as it is not always systematic, but various heuristic search algorithms have been proposed and some experimental support has been provided for them. (shrink)

Complex problem solving (CPS) emerged in the last 30 years in Europe as a new part of the psychology of thinking and problem solving. This paper introduces into the field and provides a personal view. Also, related concepts like macrocognition or operative intelligence will be explained in this context. Two examples for the assessment of CPS, Tailorshop and MicroDYN, are presented to illustrate the concept by means of their measurement devices. Also, the relation of complex cognition (...) and emotion in the CPS context is discussed. The question if CPS requires complex cognition is answered with a tentative “yes.”. (shrink)

A study is reported which focused on the problem-solving strategies employed by expert electronics engineers pursuing a real-world task: integrated-circuit design. Verbal protocol data were analysed so as to reveal aspects of the organisation and sequencing of ongoing design activity. These analyses indicated that the designers were implementing a highly systematic solution-development strategy which deviated only a small degree from a normatively optimal top-down and breadth-first method. Although some of the observed deviation could be described as opportunistic in (...) nature, much of it reflected the rapid depth-first exploration of tentative solution ideas. We argue that switches from a predominantly breadth-first mode of problem solving to depth-first or opportunistic modes may be an important aspect of the expert's strategic knowledge about how to conduct the design process effectively when faced with difficulties, uncertainties, and design impasses. (shrink)

Computer-simulated scenarios have been part of psychological research on problem solving for more than 40 years. The shift in emphasis from simple toy problems to complex, more real-life oriented problems has been accompanied by discussions about the best ways to assess the process of solving complex problems. Psychometric issues such as reliable assessments and addressing correlations with other instruments have been in the foreground of these discussions and have left the content validity of complex problem (...) class='Hi'>solving in the background. In this paper, we return the focus to content issues and address the important features that define complex problems. (shrink)

Integrative systems biology is an emerging field that attempts to integrate computation, applied mathematics, engineering concepts and methods, and biological experimentation in order to model large-scale complex biochemical networks. The field is thus an important contemporary instance of an interdisciplinary approach to solving complex problems. Interdisciplinary science is a recent topic in the philosophy of science. Determining what is philosophically important and distinct about interdisciplinary practices requires detailed accounts of problem-solving practices that attempt to understand how specific (...) practices address the challenges and constraints of interdisciplinary research in different contexts. In this paper we draw from our 5-year empirical ethnographic study of two systems biology labs and their collaborations with experimental biologists to analyze a significant problem-solving approach in ISB, which we call adaptive problem solving. ISB lacks much of the methodological and theoretical resources usually found in disciplines in the natural sciences, such as methodological frameworks that prescribe reliable model-building processes. Researchers in our labs compensate for the lack of these and for the complexity of their problems by using a range of heuristics and experimenting with multiple methods and concepts from the background fields available to them. Using these resources researchers search out good techniques and practices for transforming intractable problems into potentially solvable ones. The relative freedom lab directors grant their researchers to explore methodological options and find good practices that suit their problems is not only a response to the complex interdisciplinary nature of the specific problem, but also provides the field itself with an opportunity to discover more general methodological approaches and develop theories of biological systems. Such developments in turn can help to establish the field as an identifiably distinct and successful approach to understanding biological systems. (shrink)

Multiple theories of problem-solving hypothesize that there are distinct qualitative phases exhibited during effective problem-solving. However, limited research has attempted to identify when transitions between phases occur. We integrate theory on collaborative problem-solving with dynamical systems theory suggesting that when a system is undergoing a phase transition it should exhibit a peak in entropy and that entropy levels should also relate to team performance. Communications from 40 teams that collaborated on a complex problem (...) were coded for occurrence of problem-solving processes. We applied a sliding window entropy technique to each team's communications and specified criteria for identifying data points that qualify as peaks and determining which peaks were robust. We used multilevel modeling, and provide a qualitative example, to evaluate whether phases exhibit distinct distributions of communication processes. We also tested whether there was a relationship between entropy values at transition points and CPS performance. We found that a proportion of entropy peaks was robust and that the relative occurrence of communication codes varied significantly across phases. Peaks in entropy thus corresponded to qualitative shifts in teams’ CPS communications, providing empirical evidence that teams exhibit phase transitions during CPS. Also, lower average levels of entropy at the phase transition points predicted better CPS performance. We specify future directions to improve understanding of phase transitions during CPS, and collaborative cognition, more broadly. (shrink)

Recent research on human problem solving has largely focused on laboratory tasks that do not demand from the subject much prior, task‐related information. This study seeks to extend the theory of human problem solving to semantically richer domains that are characteristic of professional problem solving. We discuss the behavior of a single subject solving problems in chemical engineering thermodynamics. We use as a protocol‐encoding device a computer program called SAPA which also doubles as (...) a theory of the subject's problem‐solving behavior. The subject made extensive use of means‐ends analysis, similar to that observed in semantically less rich domains, supplemented by recognition mechanisms for accessing information in semantic memory. (shrink)

The aim of this paper is to describe the way in which argumentative patterns come into being in plenary debate over legislative issues in the European Parliament. What kind of argumentative patterns are to be expected within this macro context? It is shown that the argumentative patterns that come into being in legislative debate in the European Parliament depend for the most part on the problem-solving argumentation that is put forward in the opening speech by the rapporteur of (...) the parliamentary committee report. This argumentation can be pragmatic problem-solving argumentation or complex problem-solving argumentation. The most important prototypical argumentative patterns are investigated in the argumentation put forward by the Members of parliament. This investigation is based on an inventory of the arguments that can in principle be used to support or attack the initial problem-solving argumentation put forward by the rapporteur. (shrink)

The question that is the subject of this article is not intended to be a sociological or statistical question about the practice of today’s mathematicians, but a philosophical question about the nature of mathematics, and specifically the method of mathematics. Since antiquity, saying that mathematics is problem solving has been an expression of the view that the method of mathematics is the analytic method, while saying that mathematics is theorem proving has been an expression of the view that (...) the method of mathematics is the axiomatic method. In this article it is argued that these two views of the mathematical method are really opposed. In order to answer the question whether mathematics is problem solving or theorem proving, the article retraces the Greek origins of the question and Hilbert’s answer. Then it argues that, by Gödel’s incompleteness results and other reasons, only the view that mathematics is problem solving is tenable. (shrink)

In the course of daily life we solve problems often enough that there is a special term to characterize the activity and the right to expect a scientific theory to explain its dynamics. The classical view in psychology is that to solve a problem a subject must frame it by creating an internal representation of the problem‘s structure, usually called a problem space. This space is an internally generable representation that is mathematically identical to a graph structure (...) with nodes and links. The nodes can be annotated with useful information, and the whole representation can be distributed over internal and external structures such as symbolic notations on paper or diagrams. If the representation is distributed across internal and external structures the subject must be able to keep track of activity in the distributed structure. Problem solving proceeds as the subject works from an initial state in this mentally supported space, actively construction possible solution paths, evaluating them and heuristically choosing the best. Control of this exploratory process is not well understood, as it is not always systematic, but various heuristic search algorithms have been proposed and some experimental support has been provided for them. (shrink)

Creativity is commonly seen as beyond the scope of rationality. In the present paper, it is argued that available insights in epistemology and available results in logic enable us to incorporate creativity within an independently sensible view on human rationality.

A general model of problem‐solving processes based on misconception elimination is presented to simulate both impasses and solving processes. The model operates on goal‐related rules and a set of constraint rules in the form of “if (state or goal), do not (Action)” for the explicit constraints in the instructions and the implicit constraints that come from misconceptions of legal moves. When impasses occur, a constraint elimination mechanism is applied. Because successive eliminations of implicit constraints enlarge the (...) class='Hi'>problem space and have an effect on planning, the model integrates “plan‐based” and “constraint‐based” approaches to problem‐solving behavior.Simulating individual protocols of Tower of Hanoi situations shows that the model, which has a proper set of constraints, predicts a single move with no alternative on about 61% of the movements and that protocols are quite successfully simulated movement by movement. Finally, it is shown that many features of previous models are embedded in the constraint elimination model. (shrink)

This paper begins with an analysis of global problems shaping education, particularly as they impact upon learning and life chances. In addressing these problems a range of philosophical positions and controversies are considered, including: traditional romantic and institutional views of schooling; and more recent maximalist, neo-liberal, emancipatory and post-modern-perspectives of lifelong learning. In this paper we argue that these do not represent 'the last word' on the provision of learning and the enhancement of life chances and instead we put forward (...) an alternative view based upon the notion of adopting an inclusive problem-solving approach, which we believe may be better suited to offering solutions to the various global problems that have been identified or that are still emerging. We believe that such an approach addresses and expands the individual, social, economic and political features of education and conduces to the improvement and expansion of learning and life chances. (shrink)

Experimental research by social and cognitive psychologists has established that cooperative groups solve a wide range of problems better than individuals. Cooperative problem solving groups of scientific researchers, auditors, financial analysts, air crash investigators, and forensic art experts are increasingly important in our complex and interdependent society. This comprehensive textbook--the first of its kind in decades--presents important theories and experimental research about group problem solving. The book focuses on tasks that have demonstrably correct solutions within mathematical, (...) logical, scientific, or verbal systems, including algebra problems, analogies, vocabulary, and logical reasoning problems.The book explores basic concepts in group problem solving, social combination models, group memory, group ability and world knowledge tasks, rule induction problems, letters-to-numbers problems, evidence for positive group-to-individual transfer, and social choice theory. The conclusion proposes ten generalizations that are supported by the theory and research on group problem solving. Group Problem Solving is an essential resource for decision-making research in social and cognitive psychology, but also extremely relevant to multidisciplinary and multicultural problem-solving teams in organizational behavior, business administration, management, and behavioral economics. (shrink)

Problem Solving Technologies provides a user friendly understanding of technological objects including what they are and how the function in our lives.

Philosophical pragmatism provides a theory and practical guidance for engaged philosophy. The movement to apply philosophy to real-world problems gained traction in the 1970s and has become an important area of philosophical inquiry. Applied philosophy draws connections between philosophical principles and real-life problems. This has been a valuable methodology for many purposes, and it especially serves the purposes of philosophers. Unfortunately, it often starts from existing frameworks or principles that are recognized by philosophers but does not start from real-life problems (...) as they are experienced by people. Indeed, sometimes people observe miscommunication and disconnections but are not clear what the source of the problem is. Identifying the nature of a social problem from the perspective of the people who deal with it is a large part of what is required to then analyze the problem philosophically. This requires communicating directly with practitioners, policymakers, and researchers in the field at issue. Paul Thompson’s engaged philosophical approach to agricultural ethics demonstrates the diversity of philosophical activities that are required to accomplish this goal, and it is rooted in pragmatism. Engaged philosophy is more expansive than applied philosophy because it serves many functions and the frameworks produced are emergent rather than prescribed. Engaged philosophy offers an implicit critique of contemporary norms of applied philosophical practice, and it opens up creative opportunities for philosophers to engage in real-life problem solving. This essay traces Paul Thompson’s strategies for engaged philosophy and their relation to pragmatism. (shrink)

Anders, Rudi To solve a problem such as wars between nations and civil wars it is necessary to discover what causes the problem.

This paper presents an analysis of emotional and affectively toned discourse in biomedical engineering researchers’ accounts of their problem solving practices. Drawing from our interviews with scientists in two laboratories, we examine three classes of expression: explicit, figurative and metaphorical, and attributions of emotion to objects and artifacts important to laboratory practice. We consider the overall function of expressions in the particular problem solving contexts described. We argue that affective processes are engaged in problem (...) class='Hi'>solving, not as simply tacked onto reasoning but as integral to it. The examples we present illustrate the close relation of emotion to problem solving and experimentation; they also implicate social and cultural dimensions of emotion expression. The analysis underscores a need to consider emotional expression to be intimately and importantly tied to the cognitive achievements and social negotiations of laboratory practices. (shrink)

The current study describes the implementation of an online Future Problem Solving program in the field of Health education and set out to explore its contribution to students' eHealth Literacy identity, by using two levels of teacher guidance: minimal vs. frequent. FPS was employed in two groups of Health students. In the research group, frequent weekly guidance was provided to the students centered on the enhancement of eHealth Literacy skills, whereas in the control group minimal guidance was offered (...) by the lecturer. Data for the analysis were gathered from 113 Israeli undergraduate students of a Management of Health Service Organizations program, of whom 62 comprised the research group. Data were gathered twice, pre- and post-program implementation from both groups. Findings showed significant differences between the tests only for the research group, with increased levels of eHealth Literacy skills detected between the tests. The perception of the FPS program as meaningful contributed to students' perceived eHealth Literacy skills only in the research group whereas non-significant results were shown for the control group. This study mainly shows that the enhancement of skills in online educational environments requires frequent and personalized guidance. Faculty must recognize the role of the instructor as a facilitator of learning and design successful scaffolding strategies to nurture students' lifelong learning skills during distance learning. (shrink)

Sign-theoretical concepts have been used in research into the nature of living systems, not only by biologists, semioticians, and philosophers, but also by scientists who analyze organisms from the perspective of Decision Theory. Decision Theory (DT) describes both the external behavior and the internal information-processing of any kind of agent in terms of problem solving. Such “problem solving” is considered a complex process of: (1) defining a goal in an environment, (2) selecting the means to reach (...) the defined goal, and (3) controlling the effects of said selected means on the environment. The hypothesis that problem-solving agents are, first, physical entities and, second, sign-using systems is one of the most influential ideas in Decision Theory. This idea has been developed under the name of the ‘Physical Symbol System Hypothesis’ (PSSH) since the 1950s, particularly by two American scientists, Allen Newell and Herbert A. Simon, who did interdisciplinary research in cognitive science, artificial intelligence, economics, and decision theory. This paper first gives a short overview of the basic semiotic theory that underlies Newell’s and Simon’s work, and then offers some ideas on a specifically biosemiotic use of the Physical SymbolSystem Hypothesis. (shrink)

In the movie The Gold Rush Charlie Chaplin and his friend are stranded in a log cabin in the middle of winter while a blizzard rages. The cabin is isolated, and they have a very big problem – there is nothing to eat. They pace around wondering what to do. Charlie's friend starts to see Charlie as a chicken, and he tries to kill him. He chases Charlie around the cabin many times. Eventually they hit upon the idea of (...) boiling an old boot and eating it for dinner. With great delicacy they sit at the table and eat the boot as if it were a gourmet meal. They solved the problem of having nothing to eat. While their solution to the problem did not result in a culinary feast, this example reveals two crucial features of problem solving. First, a problem exists when a goal must be achieved and the solution is not immediately obvious. Second, problem solving often involves attempting different ways to solve the problem. Put more formally, a problem has four components. First, there is an initial state. This is the person's state of knowledge at the start of a problem. Second, there is the goal state: the goal that the person wishes to achieve. Third are the actions or operations that the problem‐solver can use to get to the goal state. Fourth is the task environment that the solver is working in. The task environment consists of the features of the physical environment that can either directly or indirectly constrain or suggest different ways of solving a problem. I will sketch out the main currents of thinking in research in this area, beginning by reviewing the history of research on problem solving and then focusing on a number of important issues in problem‐solving research. Finally, I will give an overview of some recent developments. (shrink)

In adversarial problem solving (APS), one must anticipate, understand and counteract the actions of an opponent. Military strategy, business, and game playing all require an agent to construct a model of an opponent that includes the opponent's model of the agent. The cognitive mechanisms required for such modeling include deduction, analogy, inductive generalization, and the formation and evaluation of explanatory hypotheses. Explanatory coherence theory captures part of what is involved in APS, particularly in cases involving deception.