Introduction: Swarm-based gradient descent for non convex optimization
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arXiv
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866911819996594176 |
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| author | Tikko, Janina |
| author_facet | Tikko, Janina |
| contents | The field of optimization has the goal to find an optimal solution to a target function, i.e. to minimize (or maximize) the target function. When trying to find such a global minimum, one often encounters local minima due to unfavorable procedures and starting regions. The swarm-based gradient descent method of Prof. Eitan Tadmor offers an alternative method for solving global minimization problems. By using a swarm of agents, local minima will not be taken account and the global minimum will be found. Furthermore leads the communication between the agent to a further expansion of the search region. Under the supervision of Prof. Angela Kunoth, I give an introduction to this swarm-based method in my bachelor thesis. Therefore I used my own program in Julia to give a more visual understanding of how the new method works and which influence certain parameters such as the number of agents or "q" have. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_00005 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Introduction: Swarm-based gradient descent for non convex optimization Tikko, Janina Optimization and Control 65K10 The field of optimization has the goal to find an optimal solution to a target function, i.e. to minimize (or maximize) the target function. When trying to find such a global minimum, one often encounters local minima due to unfavorable procedures and starting regions. The swarm-based gradient descent method of Prof. Eitan Tadmor offers an alternative method for solving global minimization problems. By using a swarm of agents, local minima will not be taken account and the global minimum will be found. Furthermore leads the communication between the agent to a further expansion of the search region. Under the supervision of Prof. Angela Kunoth, I give an introduction to this swarm-based method in my bachelor thesis. Therefore I used my own program in Julia to give a more visual understanding of how the new method works and which influence certain parameters such as the number of agents or "q" have. |
| title | Introduction: Swarm-based gradient descent for non convex optimization |
| topic | Optimization and Control 65K10 |
| url | https://arxiv.org/abs/2404.00005 |