Liu, K.; Bi, Y.; Zhang, Q.; Li, J. A Source Seeking Method for the Implicit Information Field Based on a Balanced Searching Strategy. Electronics2023, 12, 3027.
Liu, K.; Bi, Y.; Zhang, Q.; Li, J. A Source Seeking Method for the Implicit Information Field Based on a Balanced Searching Strategy. Electronics 2023, 12, 3027.
Liu, K.; Bi, Y.; Zhang, Q.; Li, J. A Source Seeking Method for the Implicit Information Field Based on a Balanced Searching Strategy. Electronics2023, 12, 3027.
Liu, K.; Bi, Y.; Zhang, Q.; Li, J. A Source Seeking Method for the Implicit Information Field Based on a Balanced Searching Strategy. Electronics 2023, 12, 3027.
Abstract
To solve the problem of low efficiency of source seeking in implicit information field, this paper presents an autonomous souring method based on balanced searching strategy is enlighten by biological homing behaviors. At the beginning of the research, the source seeking task come down to a multi-objective convergence issue. By taking the feasibility search behaviors as the individual sample of the evolutionary population drawing on the thought of evolutionary algorithms, then combine motion searching with population evolution, so the carrier can be guide to complete source seeking task by solving the multi-objective problem. Furthermore, the distribution entropy is also considerated d to measure the searching bias in the process of source seeking. Combined with the demand of the source seeking process, a new source seeking method of balanced searching strategy is designed. Ultimately, through theoretical analysis and simulation verification confirm the effectiveness and rationality of the proposed method.
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
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