Results 21 to 30 of about 3,608,849 (131)

Inducing decision trees with an ant colony optimization algorithm [PDF]

, 2012
Decision trees have been widely used in data mining and machine learning as a comprehensible knowledge representation. While ant colony optimization (ACO) algorithms have been successfully applied to extract classification rules, decision tree induction ...
Otero, Fernando E.B., Johnson, Colin G., Freitas, Alex A.   +2 more
core   +1 more source

A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines

Advanced Intelligent Systems, EarlyView.
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe, Eleonora Raimondo, Andrea Grimaldi, Pedram Khalili Amiri, Stefano Chiappini, Anna Giordano, Mario Carpentieri, Hyunsoo Yang, Massimo Chiappini, Giovanni Finocchio   +9 more
wiley   +1 more source

Revisiting Trace and Testing Equivalences for Nondeterministic and Probabilistic Processes [PDF]

, 2012
One of the most studied extensions of testing theory to nondeterministic and probabilistic processes yields unrealistic probabilities estimations that give rise to two anomalies. First, probabilistic testing equivalence does not imply probabilistic trace
Nicola Michele Loreti, Rocco Nicola, De Nicola, Rocco, Marco Bernardo, Rocco De, Loreti, Michele, Rocco De Nicola, Michele Loreti, Bernardo, Marco, De Nicola, R   +9 more
core   +1 more source

Emerging applications of large language models in ecology and conservation science

Conservation Biology, EarlyView.
Abstract Large language models (LLMs) mark a major development in artificial intelligence, with potentially transformative implications for ecology and conservation science. Built on advanced deep‐learning architectures, these models can support a wide range of tasks. We reviewed emerging applications of LLMs, drawing on the wider scientific literature
Christos Mammides, Hao Gu, Thilina S. Nimalrathna, Naufal Rahman Avicena, Harris Papadopoulos, Ahimsa Campos‐Arceiz   +5 more
wiley   +1 more source

Large Language Models and Agentic AI for Vulnerability Management: A Systematic Review

Expert Systems, Volume 43, Issue 11, November 2026.
ABSTRACT Large Language Models (LLMs), pretrained language and code models and agentic artificial intelligence are increasingly being investigated across the vulnerability‐management lifecycle. However, the evidence remains fragmented across code‐level prediction, vulnerability‐intelligence enrichment, exploit‐oriented evaluation, automated repair and ...
Yasamin Akrami, Malek Malkawi, Reda Alhajj   +2 more
wiley   +1 more source

Interactive-Decision-Trees

, 2021
This is the first release of Interactive Decision Trees package. It contains Python modules that enable the user to interact with the Decision Tree by creating new composite variables, grouping the input variables and color code the groups, selecting ...
Pianosi, Francesca, Sarailidis, Georgios, Wagener, Thorsten   +2 more
core   +1 more source

Accelerated Parameter Optimization of Granular Models of Battery Manufacturing

Batteries &Supercaps, Volume 9, Issue 10, October 2026.
Aiming to overcome classical traditional approaches disadvantages in automating parameter searches, this study introduces an asynchronous particle swarm optimizer that aims to explore a collection of simulation variables to achieve correlation with a macroscopic target property. The optimiser shown here runs across hundreds of cores on HPC environments,
Sourab Barath Vijayaraghavan, Soorya Saravanan, Mohammed Alabdali, Pei Sun, Alejandro A. Franco   +4 more
wiley   +1 more source

Alternating model trees [PDF]

, 2015
Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes.
Kramer, Stefan, Eibe Frank, Michael Mayo, Mayo, Michael, Frank, Eibe, Stefan Kramer   +5 more
core   +1 more source

Reinforcement Learning With Timed Constraints for Robotics Motion Planning

Artificial Intelligence for Engineering, Volume 2, Issue 3, Page 209-222, September 2026.
This work presents a unified automata‐based reinforcement learning framework that enforces MITL time‐bounded task specifications in both MDPs and POMDPs. Results from grid‐world and office scenarios show robust policy learning under stochastic dynamics and partial observability.
Zhaoan Wang, Junchao Li, Mohammad Mahdi Dehghan Pir, Shaoping Xiao   +3 more
wiley   +1 more source

Harnessing Generative AI Within Human‐Aligned Constraints: Exploring Control Strategies and Existential Considerations

Engineering Reports, Volume 8, Issue 7, July 2026.
We propose the Powerful‐but‐Limited Generative AI theorem, demonstrating that embedding human‐inspired constraints, such as fixed utility functions and neuro‐symbolic submission layers, ensures generative AI remains controllable by preventing self‐improvement beyond designer intent.
Saeed Banaeian Far, Mohammad Reza Chalak Qazani, Falah Younis Hamode Hamod, Azadeh Imani Rad   +3 more
wiley   +1 more source