In this work, we take into account the Fireworks Algorithm and the Particle Swarm Optimization in order to compare their exploration and exploitation capabilities. In particular, the investigation is performed considering as complex global optimization problem the estimation of the parameters of the ...
However, it has been well acknowledged that a clear identification of the exploration and exploitation phases is not possible. It is still an open question on how to measure the balance [3]. In EAs for single-objective optimization, the population diversity in the search space is usually ...
总体的模块图如下所示，VAM 即上面提到的基于 list-wise 优选做 exploitation 模块，HBM 则是基于 badn...
1. Definition and Core Concepts of Geophysical ExplorationGeophysical Exploration, also known asgeophysi...
Human development is often described as a ‘cooling off’ process, analogous to stochastic optimization algorithms that implement a gradual reduction in randomness over time. Yet there is ambiguity in how to interpret this analogy, due to a lack of concr
18. With the development of oil exploration and drilling technology level, high-viscosity and high pour point crude exploitation is in an increasing proportion. 中文摘要:随着石油开采和钻井技术水平的提高,高粘度、高凝固点原油的开采比例越来越大。
In order to introduce this crucial concept of this work it is useful to say at the outset that the notion of optimal modularity is rarely used in engineering design7. The modularity optimization problem has quite long history, and it includes several methods for detecting communities in complex ...
The problem of optimally balancing exploration and exploitation in multi-agent systems (MAS) has been a fundamental motivating driver of online learning, optimization theory and evolutionary game theory [1], [2]. From a behavioral perspective, it involves the design of realistic models to capture ...
The imbalance of exploration and exploitation has long been a significant challenge in reinforcement learning. In policy optimization, excessive reliance on exploration reduces learning efficiency, while over-dependence on exploitation might trap agents in local optima. This paper revisits the exploration-...
To solve this extremely complex problem, we propose a Bayesian optimization method that dynamically trades off exploration (minimizing uncertainty in unknown parts of the policy space) and exploitation (capitalizing on the current best solution). We demonstrate our approach with a visually-guide mobile...