Proceedings ArticleDOI
Genetic network programming - application to intelligent agents
Hironobu Katagiri,K. Hirasama,J. Hu +2 more
- Vol. 5, pp 3829-3834
TLDR
This work proposes a new method, genetic network programming (GNP), which is composed of plural nodes for agents to execute simple judgment/processing and they are connected with each other to form a network structure.Abstract:
Recently many studies have been made on the automatic design of complex systems using evolutionary optimization techniques such as genetic algorithms (GA), evolution strategy (ES), evolutionary programming (EP) and genetic programming (GP). It is generally recognized that these techniques are very useful for optimizing fairly complex systems such as the generation of intelligent behavior sequences of robots. A new method, genetic network programming (GNP), is proposed in order to acquire these behavior sequences efficiently. GNP is composed of plural nodes for agents to execute simple judgment/processing and they are connected with each other to form a network structure. Agents behave according to the contents of the nodes and their connections in GNP. In order to obtain a better structure, the GNP changes itself using evolutionary optimization techniques.read more
Citations
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Journal ArticleDOI
A Graph-Based Evolutionary Algorithm: Genetic Network Programming (GNP) and Its Extension Using Reinforcement Learning
TL;DR: An extended algorithm, GNP with Reinforcement Learning (GNPRL) is proposed which combines evolution and reinforcement learning in order to create effective graph structures and obtain better results in dynamic environments.
Journal ArticleDOI
A study of evolutionary multiagent models based on symbiosis
TL;DR: Simulation results show that Masbiole can obtain various kinds of behaviors and better performances than conventional MAS in MTT by evolution, and its characteristics are examined especially with an emphasis on the behaviors of agents obtained by symbiotic evolution.
Proceedings ArticleDOI
Comparison between Genetic Network Programming (GNP) and Genetic Programming (GP)
TL;DR: A novel evolutionary method named Genetic Network Programming (GNP), whose genome is a network structure is proposed to overcome the low searching efficiency of GP and is applied to the problem of the evolution of ant behavior in order to study the effectiveness of GNP.
Journal ArticleDOI
Application of evolutionary computation for rule discovery in stock algorithmic trading
TL;DR: The review reveals the research focus and gaps in applying EC techniques for rule discovery in stock AT and suggests a roadmap for future research.
References
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Evolutionary programming made faster
Xin Yao,Yong Liu,Guangming Lin +2 more
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PADO: a new learning architecture for object recognition
Astro Teller,Manuela Veloso +1 more
TL;DR: m n oLprq_stpvu wyx!u=q_zKu={|pv}!z~zu_}{|xa}\oLo; pv}1o
pvn!Bq_ -n_s n_{o;u=z
Journal ArticleDOI
Evolutionary learning of communicating agents
TL;DR: The emergence of the cooperative behavior for communicating agents by means of Genetic Programming is presented and the effectiveness of the emergent communication in terms of the robustness of generated GP programs is shown.