Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Aranha, Claus"'
Autor:
He, Yifan, Aranha, Claus
In this study, we use Genetic Programming (GP) to compose new optimization benchmark functions. Optimization benchmarks have the important role of showing the differences between evolutionary algorithms, making it possible for further analysis and co
Externí odkaz:
http://arxiv.org/abs/2403.14146
Publikováno v:
In Proceedings of the Companion Conference on Genetic and Evolutionary Computation (GECCO '23 Companion). Association for Computing Machinery, New York, NY, USA, (2023) 503-506
Dynamic Optimization Problems (DOPs) are characterized by changes in the fitness landscape that can occur at any time and are common in real world applications. The main issues to be considered include detecting the change in the fitness landscape an
Externí odkaz:
http://arxiv.org/abs/2310.05505
The performance of multiobjective evolutionary algorithms (MOEAs) varies across problems, making it hard to develop new algorithms or apply existing ones to new problems. To simplify the development and application of new multiobjective algorithms, t
Externí odkaz:
http://arxiv.org/abs/2308.02527
Autor:
Tanaka, Fabio, Aranha, Claus
When simulating soft robots, both their morphology and their controllers play important roles in task performance. This paper introduces a new method to co-evolve these two components in the same process. We do that by using the hyperNEAT algorithm t
Externí odkaz:
http://arxiv.org/abs/2212.11517
We apply the knowledge of urban settings established with the study of Land Use and Transport Interaction (LUTI) models to develop reward functions for an agent-based system capable of planning realistic artificial cities. The system aims to replicat
Externí odkaz:
http://arxiv.org/abs/2211.01959
We introduce Knowledge-Driven Program Synthesis (KDPS) as a variant of the program synthesis task that requires the agent to solve a sequence of program synthesis problems. In KDPS, the agent should use knowledge from the earlier problems to solve th
Externí odkaz:
http://arxiv.org/abs/2209.03736
Autor:
Khan, Mohiuddeen, Aranha, Claus
Werewolf is a popular party game throughout the world, and research on its significance has progressed in recent years. The Werewolf game is based on conversation, and in order to win, participants must use all of their cognitive abilities. This comm
Externí odkaz:
http://arxiv.org/abs/2205.09813
The performance of multiobjective algorithms varies across problems, making it hard to develop new algorithms or apply existing ones to new problems. To simplify the development and application of new multiobjective algorithms, there has been an incr
Externí odkaz:
http://arxiv.org/abs/2203.13447
Understanding the search dynamics of multiobjective evolutionary algorithms (MOEAs) is still an open problem. This paper extends a recent network-based tool, search trajectory networks (STNs), to model the behavior of MOEAs. Our approach uses the ide
Externí odkaz:
http://arxiv.org/abs/2201.11726