When incorporating the environment into mental processing (cf., cognitive offloading), one creates novel cognitive strategies that have the potential to improve task performance. Improved performance can, for example, mean faster problem solving, more accurate solutions, or even higher grades at university.1 Although cognitive offloading has frequently been associated with improved performance, it is yet unclear how flexible problem solvers are at matching their offloading habits with their current performance goals (can people improve goal‐related instead of generic performance, e.g., when being (...) in a hurry and aiming for a “quick and dirty” solution?). Here, we asked participants to solve a cognitive task, provided them with different goals—maximizing speed (SPD) or accuracy (ACC), respectively—and measured how frequently (Experiment 1) and how proficiently (Experiment 2) they made use of a novel external resource to support their cognitive processing. Experiment 1 showed that offloading behavior varied with goals: Participants offloaded less in the SPD than in the ACC condition. Experiment 2 showed that this differential offloading behavior was associated with high goal‐related performance: fast answers in the SPD, accurate answers in the ACC condition. Simultaneously, goal‐unrelated performance was sacrificed: inaccurate answers in the SPD, slow answers in the ACC condition. The findings support the notion of humans as canny offloaders who are able to successfully incorporate their environment in pursuit of their current cognitive goals. Future efforts should be focused on the finding's generalizability, for example, to settings without feedback or with high mental workload. (shrink)

Straipsnyjc svarstornas Algio Micklino atsakas huscrliSkosios fcnorncnologijos kritikarns. Autorius iSrySkina tris svarbiausius IJusscrlio kritikq argurnen- tus: 1 .IHusscrlio fcnorncnologija yra toli graiu nc "rnohlas bc jokiq ikankstiniy prielaidq", ji suponuo- ja dckartiSkqj teiginj, jog bliti rciSkia "hliti paiintu". 2.1-Tusserlio tciginj apic fcnorncnologines duotics apo- diktiSkurnq susilpnina jo patics patcikiarni tokios duo- tics apra5yrnai. IS ju, prieSingai Husserlio ketinirnarns. i6aiSkcja fenorncnologincs rcflcksijos ncpajcgurnas "susidoroti" tiek su retencine 1;iikines patirties di- rncnsija, tiek su radikalia Kito patirtics kitokybe. 3.Husscrlio rnctodui ir rnqstyrnui apskritai (...) budingas eurocentrizrnas ir episterninis irnpcrializrnas - visus kultlirinius ir istorinills skirturnus jis susurnuojn savo fenornenologijoje, kuriy traktuoja kaip slaptq graiko- curopictiSko.jo irnogaus llikcsi.iij iksipildyrnn. Algiui Micktinui svarbiausias klausirnns yra Sis: Koclkl reiketq intcrpretuoti Husserli blitent iitaip? Micktinas, Husscrlio rnokiniy Eugcno Finko ir Lud- wigo Landgrebe's rnokinys, gcrai suvokc, jog ypa- tingas Husscrlio raSyrno stilius nesyk yra veikiau su- trrlkdes nei pacle,jysvisu radikalurnu atsiskleisti svar- biausiorns Mol\qto.jo @valgorns ir atradirnarns. Tatiau jam Sis triikurnas visuornct atrodes ncrciksrningas ly- ginant su rniliiniiku potcncialu, kuris Siuosc atradi- rnuose gltidi. laukdarnas tolcsnio iiplctojirno. Hus- scrlio filosofija Micktinui yra tarsi jminirno laukiantis rnjsliy rinkinps, ir Si jrninirnq jis laiko prasrningesniu uidaviniu ui pastangas padcrnonstruoti huserliSkos fenornenologijos nenuoscklurnus ir silpnqsiasvietas. Savo darbuose Micktinas parodo. jog, ncpaisant kri- tikq iipuoliu, Husscrlio fcnorncnologinio rnctodo vi- suotinurnas ir fundamentalurnas iilicka ncpancigti. Raktiniai iodiiai: fi.nornenologija, refleksijn, skirtis, jk~~orner~ns, ~~~~enntnn.spn.snrrli.s, pntirtis. (shrink)

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The use of forward models is well established in cognitive and computational neuroscience. We compare and contrast two recent, but interestingly divergent, accounts of the place of forward models in the human cognitive architecture. On the Auxiliary Forward Model account, forward models are special-purpose prediction mechanisms implemented by additional circuitry distinct from core mechanisms of perception and action. On the Integral Forward Model account, forward models lie at the heart of all forms of perception and action. We compare these neighbouring (...) but importantly different visions and consider their implications for the cognitive sciences. We end by asking what kinds of empirical research might offer evidence favouring one or the other of these approaches. (shrink)

We are all problem-solvers of some sort. We solve problems to earn a living, get promoted, show that we are smart and deserve colleagues’ respect, and contribute to human progress. Yes, problem-solving is important; the better solution-maker we are, the brighter future we expect. But we are not such good problem solvers for simple reasons: it is hard to define a genuine problem.

This paper presents some modern and interdisciplinary concepts about creativity and creative processes specially related to problem solving. Central publications related to the theme are briefly reviewed. Creative tools and approaches suitable to support problem solving are also presented. Finally, the paper outlines the author’s experiences using creative tools and approaches to: Facilitation of problem solving processes, strategy development in organisations, design of optimisation systems for large scale and complex logistic systems, and creative design of software optimisation for complex non-linear (...) systems. (shrink)

The primary goal of ethics consultation should be to provide effective assistance to patients and families in obtaining care that is duly responsive to their rights and their needs. The consultation reported by Mark Bliton fails in this regard because it never ascertains why the consultation was called; makes little attempt to ascertain the motives of those involved; avoids exploration of the ethical concerns of family, attending or staff; makes no connection with institutional policies or practices; uncritically adopts and serves (...) the medical treatment ethos; and substitutes fellowfeeling for compassionate action. (shrink)

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 paper aims to contribute to recent critical work on the current parenting culture. It does so by a critical reading of the individual words/parts of the sentence ?Parents need to become independent problem solvers? ? a characteristic phrase of ?Triple P?, a parenting programme that has recently been implemented as a form of parenting support in a number of countries. The paper aims (1) to bring out and expose some of the worrying features of the current parenting culture, (2) (...) criticise its narrow conceptions of what a parent is and what childrearing is, (3) by doing so give a sense of the oddness of implementing Triple P as a form of parenting support and, finally, (4) tentatively suggest alternative routes of thinking for and about childrearing as well as ?grafting points? to start reconstructing parenting support practices. (shrink)

Our proposed cognitive distance learning problem solver generates sequence of actions from initial state to goal states in problem state space. This problem solver learns cognitive distance of arbitrary combination of two states. Action generation at each state is selection of next state that has minimum cognitive distance to the goal, like Q-learning agent. In this paper, first, we show that our proposed method reduces search cost than conventional search method by analytical simulation in spherical state space. Second, (...) we show that an average search cost is more reduced more the prior learning term is long and our problem solver is familiar to the environment, by a computer simulation in a tile world state space. Third, we showed that proposed problem solver is superior to the reinforcement learning techniques when goal is changed by a computer simulation. Forth, we found that our simulation result consist with psychological experimental results. (shrink)

A geometric constraint solver for finding legal configurations for an under-constrained set of geometric components is proposed. While making drawings interactively, the user usually specifies few geometric constraints explicitly because some constraints are not clear to him- or her-self, or it is not practical to specify all constraints at any early design stage. Theoretically, the full geometric constraints are necessary to define a unique layout of every geometric components, but it is naturally not given throughout the process. Therefore, in (...) such an under-constrained situation, the lack of constraints must be supplemented properly to determine the final layout of components remaining undefined. For this purpose, we propose a geometric constraint solver that works in two phases: the former is to satisfy all the explicit constraints imposed by the user, and the latter is to choose appropriate value instances for every geometric component whose layout is not yet determined. We implemented a constraint-based interactive system for designing line drawings which is composed of the solver and the interactive module to let the user input geometric modi.cation commands incrementally, and proved its effectiveness by some experiments. (shrink)

There has been considerable discussion in the past about the assumptions and basis of different ethical rules. For instance, it is commonplace to say that ethical rules are defaults rules, which means that they tolerate exceptions. Some authors argue that morality can only be grounded in particular cases while others defend the existence of general principles related to ethical rules. Our purpose here is not to justify either position, but to try to model general ethical rules with artificial intelligence formalisms (...) and to compute logical consequences of different ethical theories. More precisely, this is an attempt to show that progress in non-monotonic logics, which simulates default reasoning, could provide a way to formalize different ethical conceptions. From a technical point of view, the model developed in this paper makes use of the Answer Set Programming (ASP) formalism. It is applied comparatively to different ethical systems with respect to their attitude towards lying. The advantages of such formalization are two-fold: firstly, to clarify ideas and assumptions, and, secondly, to use solvers to derive consequences of different ethical conceptions automatically, which can help in a rigorous comparison of ethical theories. (shrink)

A person's cognitive map, or knowledge of large‐scale space, is built up from observations gathered as he travels through the environment. It acts as a problem solver to find routes and relative positions, as well as describing the current location. The TOUR model captures the multiple representations that make up the cognitive map, the problem‐solving strategies it uses, and the mechanisms for assimilating new information. The representations have rich collections of states of partial knowledge, which support many of the (...) performance characteristics of common‐sense knowledge. (shrink)

This book stands at the intersection of two topics: the decidability and computational complexity of hybrid logics, and the deductive systems designed for them. Hybrid logics are here divided into two groups: standard hybrid logics involving nominals as expressions of a separate sort, and non-standard hybrid logics, which do not involve nominals but whose expressive power matches the expressive power of binder-free standard hybrid logics.The original results of this book are split into two parts. This division reflects the division of (...) the book itself. The first type of results concern model-theoretic and complexity properties of hybrid logics. Since hybrid logics which we call standard are quite well investigated, the efforts focused on hybrid logics referred to as non-standard in this book. Non-standard hybrid logics are understood as modal logics with global counting operators ) whose expressive power matches the expressive power of binder-free standard hybrid logics. The relevant results comprise: 1. Establishing a sound and complete axiomatization for the modal logic K with global counting operators ), which can be easily extended onto other frame classes, 2. Establishing tight complexity bounds, namely NExpTime-completeness for the modal logic with global counting operators defined over the classes of arbitrary, reflexive, symmetric, serial and transitive frames ), MT), MD), MB), MK4) with numerical subscripts coded in binary. Establishing the exponential-size model property for this logic defined over the classes of Euclidean and equivalential frames ), MS5).Results of the second type consist of designing concrete deductive systems for standard and non-standard hybrid logics. More precisely, they include: 1. Devising a prefixed and an internalized tableau calculi which are sound, complete and terminating for a rich class of binder-free standard hybrid logics. An interesting feature of indicated calculi is the nonbranching character of the rule, 2. Devising a prefixed and an internalized tableau calculi which are sound, complete and terminating for non-standard hybrid logics. The internalization technique applied to a tableau calculus for the modal logic with global counting operators is novel in the literature, 3. Devising the first hybrid algorithm involving an inequality solver for modal logics with global counting operators. Transferring the arithmetical part of reasoning to an inequality solver turned out to be sufficient in ensuring termination.The book is directed to philosophers and logicians working with modal and hybrid logics, as well as to computer scientists interested in deductive systems and decision procedures for logics. Extensive fragments of the first part of the book can also serve as an introduction to hybrid logics for wider audience interested in logic.The content of the book is situated in the areas of formal logic and theoretical computer science with some elements of the theory of computational complexity. (shrink)

What is the value of having medical students engage in creative production as part of their learning? Creating something new requires medical students to take risks and even to fail--something they tend to be neither accustomed to nor comfortable with doing. “Making stuff” can help students prepare for such failures in a controlled environment that doesn’t threaten their professional identities. Furthermore, doing so can facilitate students becoming resilient and creative problem-solvers who strive to find new ways to address vexing questions. (...) Though creating something new can be fun, this is not the main outcome of interest. Rather, the principle reason we recommend devoting precious curricular time to creative endeavors is because it helps medical students become better doctors. (shrink)

We describe a set of two computer‐implemented models that solve physics problems in ways characteristic of more and less competent human solvers. The main features accounting for different competences are differences in strategy for selecting physics principles, and differences in the degree of automation in the process of applying a single principle. The models provide a good account of the order in which principles are applied by human solvers working problems in kinematics and dynamics. They also are sufficiently flexible to (...) allow easy extension to several related domains of physics problems. (shrink)

Behavior that solves a problem is distinguished by the fact that it changes another part of the solver's behavior and is strengthened when it does so. Problem solving typically involves the construction of discriminative stimuli. Verbal responses produce especially useful stimuli, because they affect other people. As a culture formulates maxims, laws, grammar, and science, its members behave more effectively without direct or prolonged contact with the contingencies thus formulated. The culture solves problems for its members, and does so (...) by transmitting the verbal discriminative stimuli called rules. Induction, deduction, and the construction of models are ways of producing rules. Behavior that solves a problem may result from direct shaping by contingencies or from rules constructed either by the problem solver or by others. Because different controlling variables are involved, contingency-shaped behavior is never exactly like rule-governed behavior. The distinction must take account of a system which establishes certain contingencies of reinforcement, such as some part of the natural environment, a piece of equipment, or a verbal community; the behavior shaped and maintained by these contingencies; rules, derived from the contingencies, which specify discriminative stimuli, responses, and consequences, and the behavior occasioned by the rules. (shrink)

Following Marr’s famous three-level distinction between explanations in cognitive science, it is often accepted that focus on modeling cognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that the complexity of the task of solving a problem can be characterized by the computational complexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus engage in cognitive processes that (...) make their problem solving algorithms computationally suboptimal, in contrast with the optimal algorithms studied in the computational approach. Therefore, in order to accurately model the human cognitive tasks involved in mathematical problem solving, we need to expand our methodology to also include aspects relevant to the algorithmic level. This allows us to study algorithms that are cognitively optimal for human problem solvers. Since problem solving methods are not universal, I propose that they should be studied in the framework of enculturation, which can explain the expected cultural variance in the humanly optimal algorithms. While mathematical problem solving is used as the case study, the considerations in this paper concern modeling of cognitive tasks in general. (shrink)

ABSTRACTSkepticism about citizen competence is a core component of Christopher H. Achen and Larry M. Bartels’s call, in Democracy for Realists, for rethinking our model of democracy. In this paper I suggest that the evidence for citizen incompetence is not as clear as we might think; important research shows that we are good group problem solvers even if we are poor solitary truth seekers. I argue that deliberative democracy theory has a better handle on this fundamental fact of human cognition (...) and therefore has a more realistic view of the conditions that might improve citizen competence. (shrink)

Answer-set programming (ASP) has emerged as a declarative programming paradigm where problems are encoded as logic programs, such that the so-called answer sets of theses programs represent the solutions of the encoded problem. The efficiency of the latest ASP solvers reached a state that makes them applicable for problems of practical importance. Consequently, problems from many different areas, including diagnosis, data integration, and graph theory, have been successfully tackled via ASP. In this work, we present such ASP-encodings for problems associated (...) to abstract argumentation frameworks (AFs) and generalisations thereof. Our encodings are formulated as fixed queries, such that the input is the only part depending on the actual AF to process. We illustrate the functioning of this approach, which is underlying a new argumentation system called ASPARTIX in detail and show its adequacy in terms of computational complexity. (shrink)

This study explores the way that belief systems, interactions with social or experimental environments, and skills at the “control” level in decision‐making shape people's behavior as they solve problems. It is argued that problem‐solvers' beliefs (not necessarily consciously held) about what is useful in mathematics may determine the set of “cognitive resources” at their disposal as they do mathematics. Such beliefs may, for example, render inaccessible to them large bodies of information that are stored in long‐term memory and that are (...) easily retrieved in other circumstances. In other cases, individuals' reactions to an experimental setting (fear of failure, or the desire to “look mathematical” while being videotaped) may induce behavior that is almost pathological—and at the same time, so consistent that it can be modeled. In general, such “environmental” factors establish the context within which individuals access and utilize the information potentially at their disposal.Protocols illustrating these points are presented and discussed. A model based on an axiomatization of students' beliefs about plane geometry is outlined, and is shown to correspond closely to their problem‐solving performance. A framework is offered for analyzing problem‐solving performance at three qualitatively different levels: access to cognitive resources stored in LTM, executive or control decision‐making, and belief systems. (shrink)

This paper describes a generative theory of bugs. It claims that all bugs of a procedural skill can be derived by a highly constrained form of problem solving acting on incomplete procedures. These procedures are characterized by formal deletion operations that model incomplete learning and forgetting. The problem solver and the deletion operator have been constrained to make it impossible to derive “star‐bugs”—algorithms that are so absurd that expert diagnosticians agree that the alogorithm will never be observed as a (...) bug. Hence, the theory not only generates the observed bugs, it fails to generate star‐bugs.The theory has been tested on an extensive data base of bugs for multidigit subtraction that was collected with the aid of the diagnostic systems buggy and debuggy. In addition to predicting bug occurrence, by adoption of additional hypotheses, the theory also makes predictions about the frequency and stability of bugs, as well as the occurrence of certain latencies in processing time during testing. Arguments are given that the theory can be applied to domains other than subtraction and that it can be extended to provide a theory of procedural learning that accounts for bug acquisition. Lastly, particular care has been taken to make the theory principled so that it can not be tailored to fit any possible data. (shrink)

I argue that Hannah Arendt's analysis of the development of modern society illuminates one aspect of prevailing educational discourse. We can understand the ‘learning society’ as both an effect and an instrument of the logic of ‘bare biological life’ or zoé that Arendt claims is the ultimate point of reference for modern society. In such a society we seem to live permanently under the threat of social exclusion, being permanently put in the position of learners or problem-solvers, without the right (...) of appeal. To imagine the possibility of such an appeal requires us to recover our sense of the experience of childhood. (shrink)

The best classes have a life of their own, powered by student-led conversations that explore texts, ideas, and essential questions. In these classes, the teacher’s role shifts from star player to observer and coach as the students ▪ Think critically, ▪ Work collaboratively, ▪ Participate fully, ▪ Behave ethically, ▪ Ask and answer high-level questions, ▪ Support their ideas with evidence, and ▪ Evaluate and assess their own work. The Spider Web Discussion is a simple technique that puts this kind (...) of class within every teacher’s reach. The name comes from the weblike diagram the observer makes to record interactions as students actively participate in the discussion, lead and support one another’s learning, and build community. It’s proven to work across all subject areas and with all ages, and you only need a little know-how, a rubric, and paper and pencil to get started. As students practice Spider Web Discussion, they become stronger communicators, more empathetic teammates, better problem solvers, and more independent learners—college and career ready skills that serve them well in the classroom and beyond. Educator Alexis Wiggins provides a step-by-step guide for the implementation of Spider Web Discussion, covering everything from introducing the technique to creating rubrics for discussion self-assessment to the nuts-and-bolts of charting the conversations and using the data collected for formative assessment. She also shares troubleshooting tips, ideas for assessment and group grading, and the experiences of real teachers and students who use the technique to develop and share content knowledge in a way that’s both revolutionary and truly inspiring. (shrink)

A new theory of problem solving is presented, which embeds problem solving in the theory of action; in this theory, a problem is just a difficult action. Making this work requires a sophisticated language for‐talking about plans and their execution. This language allows a broad range of types of action, and can also be used to express rules for choosing and scheduling plans. To ensure flexibility, the problem solver consists of an interpreter driven by a theorem prover which actually (...) manipulates formulas of the language. Many examples of the use of the system six given. including an extended treatment of the world of blocks. Limitations and extensions of the system are discussed at length. It is concluded that a rule‐based problem solver is necessary and feasible, but that much more work remains to be done on the underlying theory of planning and acting. (shrink)

Benjamin Franklin famously wrote that “the good [that] men do separately is small compared with what they may do collectively” (Isaacson 2004). The ability to join with others in groups to accomplish goals collectively that would hopelessly overwhelm the time, energy, and resources of individuals is indeed one of the greatest assets of our species. In the history of humankind, groups have been among the greatest workers, builders, producers, protectors, entertainers, explorers, discoverers, planners, problem-solvers, and decision-makers. During the late 19th (...) and early 20th century, many social scientists employed the notorious “group mind” idiom to express the sensible idea that groups can function as the seats of cognition, intelligence, and agency in their own right (Allport 1968; Wilson 2004). In their quest to stress (rightly) that group phenomena are something “over and above” the sum of individual contributions, a fondness for vitalist metaphors led them to believe (wrongly) that genuine group cognition must be the result of tapping into individualistically inaccessible, “holistic” forces. Today, inspired in part by historically unparalleled forms of mass collaboration enabled by the internet, it has once again become popular to speak of collective intelligence, group agency, or even the emergence of a “global brain” (cf. the wiki-edited MIT Handbook of Collective Intelligence). -/- In this chapter, I review some contemporary developments of the idea of group cognition, defined broadly as the collaborative performance of cognitive tasks such as remembering, problem-solving, decision-making, or verbal creativity for the purpose of producing a group-level outcome. My discussion serves a two-fold purpose. First, by discussing how the idea of group cognition can be operationalized, I seek to show that we can retain some central theoretical insights of the “group mind” thesis without succumbing to its eccentric metaphysical overtones. Second, by providing a useful array of generalizable taxonomic resources, I hope to foster greater degrees of mutual awareness among insufficiently integrated areas of research on group performance. (shrink)

The usual representation of quantum algorithms, limited to the process of solving the problem, is physically incomplete. We complete it in three steps: extending the representation to the process of setting the problem, relativizing the extended representation to the problem solver to whom the problem setting must be concealed, and symmetrizing the relativized representation for time reversal to represent the reversibility of the underlying physical process. The third steps projects the input state of the representation, where the problem (...) class='Hi'>solver is completely ignorant of the setting and thus the solution of the problem, on one where she knows half solution. Completing the physical representation shows that the number of computation steps required to solve any oracle problem in an optimal quantum way should be that of a classical algorithm endowed with the advanced knowledge of half solution. (shrink)