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of 544
pro vyhledávání: '"Miikkulainen Risto"'
Solving societal problems on a global scale requires the collection and processing of ideas and methods from diverse sets of international experts. As the number and diversity of human experts increase, so does the likelihood that elements in this co
Externí odkaz:
http://arxiv.org/abs/2411.00156
Autor:
Shahrzad, Hormoz, Miikkulainen, Risto
This paper introduces an innovative approach to boost the efficiency and scalability of Evolutionary Rule-based machine Learning (ERL), a key technique in explainable AI. While traditional ERL systems can distribute processes across multiple CPUs, fi
Externí odkaz:
http://arxiv.org/abs/2406.01821
Autor:
Qiu, Xin, Miikkulainen, Risto
With the widespread application of Large Language Models (LLMs) to various domains, concerns regarding the trustworthiness of LLMs in safety-critical scenarios have been raised, due to their unpredictable tendency to hallucinate and generate misinfor
Externí odkaz:
http://arxiv.org/abs/2405.13845
Diabetes, a chronic condition that impairs how the body turns food into energy, i.e. blood glucose, affects 38 million people in the US alone. The standard treatment is to supplement carbohydrate intake with an artificial pancreas, i.e. a continuous
Externí odkaz:
http://arxiv.org/abs/2402.07949
Autor:
Miikkulainen, Risto, Francon, Olivier, Young, Daniel, Meyerson, Elliot, Schwingshackl, Clemens, Bieker, Jacob, Cunha, Hugo, Hodjat, Babak
How areas of land are allocated for different uses, such as forests, urban areas, and agriculture, has a large effect on the terrestrial carbon balance, and therefore climate change. Based on available historical data on land-use changes and a simula
Externí odkaz:
http://arxiv.org/abs/2311.12304
Many evolutionary algorithms (EAs) take advantage of parallel evaluation of candidates. However, if evaluation times vary significantly, many worker nodes (i.e.,\ compute clients) are idle much of the time, waiting for the next generation to be creat
Externí odkaz:
http://arxiv.org/abs/2308.04102
While evolutionary computation is well suited for automatic discovery in engineering, it can also be used to gain insight into how humans and organizations could perform more effectively. Using a real-world problem of innovation search in organizatio
Externí odkaz:
http://arxiv.org/abs/2306.10640
Autor:
Shahrzad, Hormoz, Miikkulainen, Risto
In building practical applications of evolutionary computation (EC), two optimizations are essential. First, the parameters of the search method need to be tuned to the domain in order to balance exploration and exploitation effectively. Second, the
Externí odkaz:
http://arxiv.org/abs/2302.06745
Autor:
Bingham, Garrett, Miikkulainen, Risto
Carefully designed activation functions can improve the performance of neural networks in many machine learning tasks. However, it is difficult for humans to construct optimal activation functions, and current activation function search algorithms ar
Externí odkaz:
http://arxiv.org/abs/2301.05785
Autor:
Qiu, Xin, Miikkulainen, Risto
Population-based search has recently emerged as a possible alternative to Reinforcement Learning (RL) for black-box neural architecture search (NAS). It performs well in practice even though it is not theoretically well understood. In particular, whe
Externí odkaz:
http://arxiv.org/abs/2210.14016