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Evolutionary multi-objective optimization of autonomous mobile robots in neural-based cognition for behavioural robustness
Published 2009“…The utilization of a multi-objective approach for evolving artificial neural networks that act as the controllers for phototaxis and radio frequency (RF) localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment is discussed in this chapter. It explains the comparison performances among the elitism without archive and elitism with archive used in the evolutionary multi-objective optimization (EMO) algorithm in an evolutionary robotics study. …”
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Chapter In Book -
2
Artificial Neural Controller Synthesis in Autonomous Mobile Cognition
Published 2009“…This paper describes a new approach in using multi-objective evolutionary algorithms in evolving the neural network that acts as a controller for the phototaxis and radio frequency localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment. …”
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Artificial Neural Controller Synthesis in Autonomous Mobile Cognition
Published 2009“…This paper describes a new approach in using multi-objective evolutionary algorithms in evolving the neural network that acts as a controller for the phototaxis and radio frequency localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment. …”
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Enhanced multi-objective evolutionary mating algorithm with improved crowding distance and levy flight for optimizing comfort index and energy consumption in smart buildings
Published 2025“…These enhancements enable MOEMA to effectively navigate complex multi-objective landscapes, leading to more diverse and well-converged Pareto-optimal solutions. The algorithm's performance is thoroughly assessed using the chosen benchmark functions and validated through practical applications in smart building environments. …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game
Published 2015“…The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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6
Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…As a result, this study has thus shown that the multi-objective approach to evolutionary robotics in the form of the elitist PDE-EMO algorithm can be practically used to automatically generate controllers for RF-Iocalization behavior in autonomous mobile robots.…”
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Research Report -
7
Walking with EMO: Multi-objective robotics for evolving two, four, and six-legged locomotion
Published 2008“…Additionally, the operational dynamics of these evolved Pareto controllers in noisy and uncertain environments, limb dynamics and effects of using a different underlying EMO algorithm will also be discussed.…”
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Chapter In Book -
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Coordination of PSS and PID controller for power system stability enhancement - overview
Published 2023Article -
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Automatic generation of Swarm Robotic behaviors using multi-objective evolution
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Working Paper
