Results 21 to 30 of about 3,458,167 (137)
Testing from a nondeterministic finite state machine using adaptive state counting [PDF]
The problem of generating a checking experiment from a nondeterministic finite state machine has been represented in terms of state counting. However, test techniques that use state counting traditionally produce preset test suites.
Hierons, RM
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IMPLEMENTASI METODE RANDOM FOREST DALAM MEMPREDIKSI SINYAL PERGERAKAN SAHAM
Trading involves purchasing stocks at low prices and then selling them at high prices to generate profits in a short period. Although it offers significant gains, trading is considered a high-risk activity.
MOCH. ANJAS APRIHARTHA +2 more
doaj +1 more source
Reinforcement Learning With Timed Constraints for Robotics Motion Planning
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 +3 more
wiley +1 more source
Emerging applications of large language models in ecology and conservation science
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 +5 more
wiley +1 more source
Uniform Labeled Transition Systems for Nondeterministic, Probabilistic, and Stochastic Processes [PDF]
Rate transition systems (RTS) are a special kind of transition systems introduced for defining the stochastic behavior of processes and for associating continuous-time Markov chains with process terms. The transition relation assigns to each process, for
Nicola Michele Loreti +8 more
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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 +3 more
wiley +1 more source
Narrating Entanglement Without Dehumanisation in Contemporary Eco‐Fiction
ABSTRACT This essay presents a comparative analysis of two contemporary works of eco‐fiction, Richard Powers's The Overstory (2018) and Eleanor Catton's Birnam Wood (2023). Both novels use multiperspective narration in the service of entanglement narratives, forms of storytelling that emphasise the interconnection of human and nonhuman life.
Diana Rose Newby
wiley +1 more source
HNN extensions and embedding theorems for groups
Abstract The Higman–Neumann–Neumann (HNN) paper of 1949 is a landmark of group theory in the 20th century. The proof of its main theorem covers less than a page and uses only pre‐existing technology, but the construction that it introduced, the HNN extension, quickly became one of the principal tools of combinatorial group theory, widely used to build ...
Martin R. Bridson +1 more
wiley +1 more source
Copulas for Covariate Simulation in Pharmacometrics
ABSTRACT Patient‐specific covariates are commonly incorporated in pharmacometric and quantitative system pharmacology models to predict differences in pharmacokinetic or pharmacodynamic profiles between patients. When simulating new virtual populations of patients, generating realistic covariate sets that accurately reflect the correlation structures ...
Yuchen Guo +3 more
wiley +1 more source
A mass assignment based ID3 algorithm for decision tree induction [PDF]
A mass assignment based ID3 algorithm for learning probabilistic fuzzy decision trees is introduced. Fuzzy partitions are used to discretize continuous feature universes and to reduce complexity when universes are discrete but with large cardinalities ...
Baldwin, JF, Martin, TP, Lawry, J
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