paper-with-me

Papers

The Search for Computational Intelligence

2015-01-31 · Joseph Corneli, Ewen Maclean

We define and explore in simulation several rules for the local evolution of generative rules for 1D and 2D cellular automata. Our implementation uses strategies from conceptual blending. We discuss potential applications to modelling social dynamics.

📄 PDF Abstract BibTeX arXiv:1502.00130

Code (1)

holtzermann17/metaca 공식 구현

Similar Papers 제목 키워드 기반

Brief Review of Computational Intelligence Algorithms

2019-01-04 · Satyarth Vaidya, Arshveer Kaur, Lavika Goel

Computational Intelligence algorithms have gained a lot of attention of researchers in the recent years due to their ability to deliver near optimal solutions.

Starting a Synthetic Biological Intelligence Lab from Scratch

2024-12-18 · Md Sayed Tanveer, Dhruvik Patel, Hunter E. Schweiger, Kwaku Dad Abu-Bonsrah 외

With the recent advancements in artificial intelligence, researchers and industries are deploying gigantic models trained on billions of samples. While training these models consumes a huge amount of energy, human brains…

Intelligence as Computation

2024-05-26 · Oliver Brock

This paper proposes a specific conceptualization of intelligence as computation. This conceptualization is intended to provide a unified view for all disciplines of intelligence research. Already, it unifies several conc…

Emerging Biometrics: Deep Inference and Other Computational Intelligence

2020-06-22 · Svetlana Yanushkevich, Shawn Eastwood, Kenneth Lai, Vlad Shmerko

This paper aims at identifying emerging computational intelligence trends for the design and modeling of complex biometric-enabled infrastructure and systems. Biometric-enabled systems are evolving towards deep learning …

Machine listening intelligence

2017-06-29 · C. E. Cella

This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

Deep Learning