1,991 research outputs found
Distributed Cognition: Cognizing, Autonomy and the Turing Test
No full textSome of the papers in this special issue distribute cognition between what is going on inside individual cognizers’ heads and their outside worlds; others distribute cognition among different individual cognizers. Turing’s criterion for cognition was individual, autonomous input/output capacity. It is not clear that distributed cognition could pass the Turing Test
Offloading Cognition onto Cognitive Technology
No full text"Cognizing" (e.g., thinking, understanding, and knowing) is a mental state. Systems without mental states, such as cognitive technology, can sometimes contribute to human cognition, but that does not make them cognizers. Cognizers can offload some of their cognitive functions onto cognitive technology, thereby extending their performance capacity beyond the limits of their own brain power. Language itself is a form of cognitive technology that allows cognizers to offload some of their cognitive functions onto the brains of other cognizers. Language also extends cognizers' individual and joint performance powers, distributing the load through interactive and collaborative cognition. Reading, writing, print, telecommunications and computing further extend cognizers' capacities. And now the web, with its network of cognizers, digital databases and software agents, all accessible anytime, anywhere, has become our “Cognitive Commons,” in which distributed cognizers and cognitive technology can interoperate globally with a speed, scope and degree of interactivity inconceivable through local individual cognition alone. And as with language, the cognitive tool par excellence, such technological changes are not merely instrumental and quantitative: they can have profound effects on how we think and encode information, on how we communicate with one another, on our mental states, and on our very nature
Decision making under time pressure: an independent test of sequential sampling models
No full textChoice probability and choice response time data from a risk-taking decision-making task were compared with predictions made by a sequential sampling model. The behavioral data, consistent with the model, showed that participants were less likely to take an action as risk levels increased, and that time pressure did not have a uniform effect on choice probability. Under time pressure, participants were more conservative at the lower risk levels but were more prone to take risks at the higher levels of risk. This crossover interaction reflected a reduction of the threshold within a single decision strategy rather than a switching of decision strategies. Response time data, as predicted by the model, showed that participants took more time to make decisions at the moderate risk levels and that time pressure reduced response time across all risk levels, but particularly at the those risk levels that took longer time with no pressure. Finally, response time data were used to rule out the hypothesis that time pressure effects could be explained by a fast-guess strategy
Transformations of Boolean Functions
No full textBoolean functions are characterized by the unique structure of their solution space. Some properties of the solution space, such as the possible existence of a solution, are well sought after but difficult to obtain. To better reason about such properties, we define transformations as functions that change one Boolean function to another while maintaining some properties of the solution space. We explore transformations of Boolean functions, compactly described as Boolean formulas, where the property is to maintain is the number of solutions in the solution spaces. We first discuss general characteristics of such transformations. Next, we reason about the computational complexity of transforming one Boolean formula to another. Finally, we demonstrate the versatility of transformations by extensively discussing transformations of Boolean formulas to "blocks," which are solution spaces in which the set of solutions makes a prefix of the solution space under a lexicographic order of the variables
Tool handling and scheduling in a two-machine flexible manufacturing cell
No full textIn this paper we examine the issue of tool management in a flexible manufacturing cell. The type of system considered here is typical of mechanical manufacturing, in which large metallic parts are loaded on the machines and are not moved until processing completion. The architecture of the cell is characterized by the absence of on-board tool magazines on the machines. Although this permits the continuous maintenance and inspection of the tools and typically results in cost and workspace savings, it calls for more complex tool handling procedures. We present a heuristic to address the overall problem of assigning parts to machines, sequencing parts on each machine, and synchronizing tool movements. The results indicate that our method provides near-optimal solutions in terms of makespan and mean flow time. Further, we observe that the solution procedure is at least one order of magnitude faster than the approach currently used and also results in a much better mean flow time
Applying Ahuja-Orlin's Large Neighbourhood for Constructing Examination Timetabling Solution (Extended Abstract)
No full textS. Abdullah , S. Ahmadi 2 , E.K.Burke , M. Dror Automated Scheduling, Optimisation and Planning Research Group, School of Computer Science & Information Technology, University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham NG8 1BB, United Kingdom 2 School of Computing, De Montfort University, The Gateway, Leicester LE1 9BH, United Kingdom MIS Department, College of Business and Public Administration, University of Arizona, Tucson, Arizona 85721, USA 1
Complexity as a guide to understanding decision bias: A contribution to the favorite-longshot bias debate
No full textThis paper investigates the origins of a widespread decision bias in betting markets, the favorite-longshot bias (FLB); in particular, whether it is caused by cognitive errors on the part of bettors or by the pricing policies of bookmakers. The methodology is based on previous literature, which has suggested that: (i) races, as decision tasks for bettors, can be distinguished by their degree of complexity and their attractiveness to those with access to privileged information (insiders), (ii) cognitive errors increase as complexity increases, and (iii) bookmakers set odds in a manner to protect themselves from insiders. The degree of FLB was examined in races of varying complexity and attractiveness to insiders using a dataset of 8,545 races drawn from the parallel bookmaker and pari-mutuel markets operating in the UK in 2004. The results, interpreted in the light of the cognitive error and complexity literature, suggest that neither bettors’ nor bookmakers’ cognitive errors are the main cause of the bias. Rather, bettors’ preferences for risk and the deliberate pricing policies of bookmakers play key roles in influencing the bias in markets where bookmakers and pari-mutuel operators co-exist
Local Search Algorithms for Maximum Carpool Matching
No full textThe Maximum Carpool Matching problem is a star packing problem in directed graphs. Formally, given a directed graph G = (V, A), a capacity function c: V -> N, and a weight function w: A -> R^+, a carpool matching is a subset of arcs, M subseteq A, such that every v in V satisfies: (i) d^{in}_M(v) cdot d^{out}_M(v) = 0, (ii) d^{in}_M(v) <= c(v), and (iii) d^{out}_M(v) <= 1. A vertex v for which d^{out}_M(v) = 1 is a passenger, and a vertex for which d^{out}_M(v) = 0 is a driver who has d^{in}_M(v) passengers. In the Maximum Carpool Matching problem the goal is to find a carpool matching M of maximum total weight. The problem arises when designing an online carpool service, such as Zimride, which tries to connect between users based on a similarity function. The problem is known to be NP-hard, even in the unweighted and uncapacitated case. The Maximum Group Carpool Matching problem, is an extension of Maximum Carpool Matching where each vertex represents an unsplittable group of passengers. Formally, each vertex u in V has a size s(u) in N, and the constraint d^{in}_M(v) <= c(v) is replaced with sum_{u:(u,v) in M} s(u) <= c(v).
We show that Maximum Carpool Matching can be formulated as an unconstrained submodular maximization problem, thus it admits a 1/2-approximation algorithm. We show that the same formulation does not work for Maximum Group Carpool Matching, nevertheless, we present a local search (1/2 - epsilon)-approximation algorithm for Maximum Group Carpool Matching. For the unweighted variant of both problems when the maximum possible capacity, c_{max}, is bounded by a constant, we provide a local search (1/2 + 1/{2c_{max}} - epsilon)-approximation algorithm. We also show that the problem is APX-hard, even if the maximum degree and c_{max} are at most 3
Reassurance sociale : stabiliser les micro-assurances sante dans les pays pauvres
No full textIncluding health issues at the top of
the political agenda, is an indictor for national
development. Breaking the vicious cycle of low resources
leading to illness, and illness leading to poverty, is a
problem that all policy makers face in poor countries.
Access to decent and affordable health care is to be
facilitated by community-based institutions, which require
sustainability through social reinsurance. The authors offer
a concept as promising as original, opening a path between
traditional government-based, and market-based responses to
the lack of health care for the very poor, while maintaining
a role for the government, in furthering social goals,
through micro-insurance, but also creating a favorable
market environment. The path is a pragmatic look at what
close-to-people-needs schemes can do to fill the gap of
ill-being. The authors, however, dig deeper into the subject
in various manners: they link their analysis to the emerging
study of social capital, and the need for people to trust
their peers, and build networks with them; they also give a
strong analytical underpinning to how to insure, and
reinsure community-based financing schemes; they preempt
possible critics, by addressing the need to design early on,
an adequate regulatory framework for micro-insurance, and
reinsurance; and, they go from theory to practice, with a
thorough case study of a pilot experience in the Philippines
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