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In today's day and time solving real-world complex problems has become fundamentally vital and critical task. Many of these are combinatorial problems, where optimal solutions are sought rather than exact solutions. Traditional optimization…

Neural and Evolutionary Computing · Computer Science 2024-09-05 Pravin S Game , Vinod Vaze , Emmanuel M

Humans are routinely asked to evaluate the performance of other individuals, separating success from failure and affecting outcomes from science to education and sports. Yet, in many contexts, the metrics driving the human evaluation…

Physics and Society · Physics 2017-12-07 Luca Pappalardo , Paolo Cintia , Dino Pedreschi , Fosca Giannotti , Albert-Laszlo Barabasi

A predominant topic in the theory of evolutionary algorithms and, more generally, theory of randomized black-box optimization techniques is running time analysis. Running time analysis aims at understanding the performance of a given…

Neural and Evolutionary Computing · Computer Science 2018-06-13 Carola Doerr

Solving an optimization task in any domain is a very challenging problem, especially when dealing with nonlinear problems and non-convex functions. Many meta-heuristic algorithms are very efficient when solving nonlinear functions. A…

Neural and Evolutionary Computing · Computer Science 2020-07-28 Mona Nasr , Omar Farouk , Ahmed Mohamedeen , Ali Elrafie , Marwan Bedeir , Ali Khaled

In this work, we initiate the investigation of optimization opportunities in collaborative crowdsourcing. Many popular applications, such as collaborative document editing, sentence translation, or citizen science resort to this special…

We introduce a novel framework for incorporating human expertise into algorithmic predictions. Our approach leverages human judgment to distinguish inputs which are algorithmically indistinguishable, or "look the same" to predictive…

Machine Learning · Computer Science 2024-10-31 Rohan Alur , Manish Raghavan , Devavrat Shah

How do we predict others from patterns in their behavior and what are the computational constraints that limit this ability? We investigate these questions by modeling human behavior over repeated games of rock, paper, scissors from…

Neurons and Cognition · Quantitative Biology 2025-08-12 Logan Cross , Erik Brockbank , Tobias Gerstenberg , Judith E. Fan , Daniel L. K. Yamins , Nick Haber

Swarm intelligence is all about developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the individual contributions so that a complementary…

Neural and Evolutionary Computing · Computer Science 2015-04-23 Muharrem Düğenci

Workers spend a significant amount of time learning how to make good decisions. Evaluating the efficacy of a given decision, however, can be complicated -- e.g., decision outcomes are often long-term and relate to the original decision in…

Machine Learning · Computer Science 2024-03-20 Hamsa Bastani , Osbert Bastani , Wichinpong Park Sinchaisri

Social computation, whether in the form of searches performed by swarms of agents or collective predictions of markets, often supplies remarkably good solutions to complex problems. In many examples, individuals trying to solve a problem…

Information Theory · Computer Science 2011-03-25 Vadas Gintautas , Aric Hagberg , Luis M. A. Bettencourt

An essential task of groups is to provide efficient solutions for the complex problems they face. Indeed, considerable efforts have been devoted to the question of collective decision-making related to problems involving a single dominant…

Physics and Society · Physics 2017-04-05 Anna Zafeiris , Zsombor Koman , Enys Mones , Tamás Vicsek

Artificial intelligence algorithms are capable of fantastic exploits, yet they are still grossly inefficient compared with the brain's ability to learn from few exemplars or solve problems that have not been explicitly defined. What is the…

Neurons and Cognition · Quantitative Biology 2018-10-08 Aurelio Cortese , Benedetto De Martino , Mitsuo Kawato

Visual search is a fundamental natural task for humans and other animals. We investigated the decision processes humans use in covert (single-fixation) search with briefly presented displays having well-separated potential target locations.…

Neurons and Cognition · Quantitative Biology 2025-04-16 Anqi Zhang , Wilson S. Geisler

Human psychology plays an important role in organizational performance. However, understanding our employees is a difficult task due to issues such as psychological complexities, unpredictable dynamics, and the lack of data. Leveraging…

Computers and Society · Computer Science 2020-01-28 Tam N. Nguyen

Minimizing the number of reshuffling operations at maritime container terminals incorporates the Pre-Marshalling Problem (PMP) as an important problem. Based on an analysis of existing solution approaches we develop new heuristics utilizing…

Artificial Intelligence · Computer Science 2015-11-17 Raka Jovanovic , Milan Tuba , Stefan Voss

Human decision-making is plagued by many systematic errors. Many of these errors can be avoided by providing decision aids that guide decision-makers to attend to the important information and integrate it according to a rational decision…

Artificial Intelligence · Computer Science 2022-07-20 Frederic Becker , Julian Skirzyński , Bas van Opheusden , Falk Lieder

Most optimization problems in real life applications are often highly nonlinear. Local optimization algorithms do not give the desired performance. So, only global optimization algorithms should be used to obtain optimal solutions. This…

Neural and Evolutionary Computing · Computer Science 2012-11-28 Mohammed El-Dosuky , Ahmed EL-Bassiouny , Taher Hamza , Magdy Rashad

Humans are the most effective integrators and producers of information, directly and through the use of information-processing inventions. As these inventions become increasingly sophisticated, the substantive role of humans in processing…

Human-Computer Interaction · Computer Science 2015-05-07 Pietro Michelucci

A hallmark of human intelligence is the ability to adapt to new situations, by applying learned rules to new content (systematicity) and thereby enabling an open-ended number of inferences and actions (generativity). Here, we propose that…

Neurons and Cognition · Quantitative Biology 2021-08-10 Randall C. O'Reilly , Charan Ranganath , Jacob L. Russin

A sketch of the chapter appearing under the same heading in the book ``New Optimization Algorithms in Physics'' (A.K. Hartmann and H. Rieger, Eds.) is given. After a general introduction to spin glasses, important aspects of heuristic…

Disordered Systems and Neural Networks · Physics 2007-05-23 Olivier C. Martin