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Evolutionary search via the quality-diversity (QD) paradigm can discover highly performing solutions in different behavioural niches, showing considerable potential in complex real-world scenarios such as evolutionary robotics. Yet most QD…

神经与进化计算 · 计算机科学 2024-04-10 Roberto Gallotta , Antonios Liapis , Georgios N. Yannakakis

Metaheuristic search methods have proven to be essential tools for tackling complex optimization challenges, but their full potential is often constrained by conventional algorithmic frameworks. In this paper, we introduce a novel approach…

人工智能 · 计算机科学 2024-10-23 Abdel-Rahman Hedar , Alaa E. Abdel-Hakim , Wael Deabes , Youseef Alotaibi , Kheir Eddine Bouazza

The acquisition of competence is a key element in the ability to assert oneself in the complex and rapidly changing modern worlds of work. This paper examines the evolution of competence, i.e. the role of competences in an evolutionary…

物理与社会 · 物理学 2007-05-23 Andrea Scharnhorst , Werner Ebeling

As games challenge traditional automated white-box test generators, the Neatest approach generates test suites consisting of neural networks that exercise the source code by playing the games. Neatest generates these neural networks using…

软件工程 · 计算机科学 2024-07-09 Patric Feldmeier , Gordon Fraser

In light of Phillips' contention regarding the impracticality of Search Neutrality, asserting that non-epistemic factors presently dictate result prioritization, our objective in this study is to confront this constraint by questioning…

信息检索 · 计算机科学 2025-01-03 Shiran Dudy

Effective exploration is a key to successful search. The recently proposed Negatively Correlated Search (NCS) tries to achieve this by parallel exploration, where a set of search processes are driven to be negatively correlated so that…

神经与进化计算 · 计算机科学 2023-09-26 Peng Yang , Qi Yang , Ke Tang , Xin Yao

Many of the artificial intelligence techniques developed to date rely on heuristic search through large spaces. Unfortunately, the size of these spaces and the corresponding computational effort reduce the applicability of otherwise novel…

人工智能 · 计算机科学 2011-05-30 D. J. Cook , R. C. Varnell

A key challenge in satisficing planning is to use multiple heuristics within one heuristic search. An aggregation of multiple heuristic estimates, for example by taking the maximum, has the disadvantage that bad estimates of a single…

人工智能 · 计算机科学 2021-04-13 David Speck , André Biedenkapp , Frank Hutter , Robert Mattmüller , Marius Lindauer

This paper introduces the concept of fitness cloud as an alternative way to visualize and analyze search spaces than given by the geographic notion of fitness landscape. It is argued that the fitness cloud concept overcomes several…

人工智能 · 计算机科学 2007-09-26 Philippe Collard , Sébastien Verel , Manuel Clergue

Robustness, the insensitivity of some of a biological system's functionalities to a set of distinct conditions, is intimately linked to fitness. Recent studies suggest that it may also play a vital role in enabling the evolution of species.…

适应与自组织系统 · 物理学 2011-12-15 James M Whitacre , Axel Bender

Designing evolutionary algorithms capable of uncovering highly evolvable representations is an open challenge; such evolvability is important because it accelerates evolution and enables fast adaptation to changing circumstances. This paper…

神经与进化计算 · 计算机科学 2019-07-16 Alexander Gajewski , Jeff Clune , Kenneth O. Stanley , Joel Lehman

Many water-based optimization metaheuristics have been introduced during the last decade, both for combinatorial and for continuous optimization. Despite the strong similarities of these methods in terms of their underlying natural…

神经与进化计算 · 计算机科学 2024-03-20 Fernando Rubio , Ismael Rodríguez

Agents of any metaheuristic algorithms are moving in two modes, namely exploration and exploitation. Obtaining robust results in any algorithm is strongly dependent on how to balance between these two modes. Whale optimization algorithm as…

When searching for policies, reward-sparse environments often lack sufficient information about which behaviors to improve upon or avoid. In such environments, the policy search process is bound to blindly search for reward-yielding…

神经与进化计算 · 计算机科学 2023-07-18 Paul-Antoine Le Tolguenec , Emmanuel Rachelson , Yann Besse , Dennis G. Wilson

Wildfires are a highly prevalent multi-causal environmental phenomenon. The impact of this phenomenon includes human losses, environmental damage and high economic costs. To mitigate these effects, several computer simulation systems have…

分布式、并行与集群计算 · 计算机科学 2022-07-26 Jan Strappa , Paola Caymes-Scutari , Germán Bianchini

Recent work such as AlphaEvolve has shown that combining LLM-driven optimization with evolutionary search can effectively improve programs, prompts, and algorithms across domains. In this paradigm, previously evaluated solutions are reused…

For ambiguous queries, conventional retrieval systems are bound by two conflicting goals. On the one hand, they should diversify and strive to present results for as many query intents as possible. On the other hand, they should provide…

信息检索 · 计算机科学 2015-03-19 Karthik Raman , Thorsten Joachims , Pannaga Shivaswamy

Natural evolution has produced a tremendous diversity of functional organisms. Many believe an essential component of this process was the evolution of evolvability, whereby evolution speeds up its ability to innovate by generating a more…

神经与进化计算 · 计算机科学 2019-02-15 Joost Huizinga , Kenneth O. Stanley , Jeff Clune

Self-training systems often degenerate due to the lack of an external criterion for judging data quality, leading to reward hacking and semantic drift. This paper provides a proof-of-concept system architecture for stable self-training…

Query-based searching and browsing-based navigation are the two main components of exploratory search. Search lets users dig in deep by controlling their actions to focus on and find just the information they need, whereas navigation helps…

信息检索 · 计算机科学 2017-11-02 Mostafa Dehghani , Glorianna Jagfeld , Hosein Azarbonyad , Alex Olieman , Jaap Kamps , Maarten Marx