Achieving Swarm Intelligence with Spiking Neural Oscillators
Achieving Swarm Intelligence with Spiking Neural Oscillators
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DOI：
10.1109/icrc.2017.8123632
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发表时间：
2017-11
期刊：
影响因子：
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通讯作者：
Yan Fang;Samuel J. Dickerson
中科院分区：
文献类型：
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作者：
Yan Fang;Samuel J. Dickerson
模仿生物群体的协作行为，如鸟群和蚁群，群智能算法为各种优化问题提供了有效的解决方案。另一方面，由于最近出现了用于高效和低功耗计算的神经形态硬件，人类大脑的计算模型，尖峰神经网络，在识别，推理和学习方面表现出很大的希望。通过桥接这两个不同的研究领域，我们提出了一种新的计算范式，实现群体智能与人口的耦合尖峰神经振荡器在基本的泄漏集成和消防（LIF）模型。我们的模型表现为一个元启发式搜索进行多个协作代理。在这种设计中，振荡神经元作为群体中的代理，在频率编码中搜索解决方案，并通过尖峰信号相互通信。每个代理的发射率是自适应的其他代理与更好的解决方案和最优的解决方案呈现为群体同步。将该方法应用于多个测试目标函数的参数优化，验证了其有效性和效率。这种新的计算范式扩展了耦合尖峰神经元在求解优化问题领域的计算能力，为个体智能和群体智能之间的连接带来了机会。
Mimicking the collaborative behavior of biological swarms, such as bird flocks and ant colonies, Swarm Intelligence algorithms provide efficient solutions for various optimization problems. On the other hand, a computational model of the human brain, spiking neural networks, has been showing great promise in recognition, inference, and learning, due to recent emergence of neuromorphic hardware for high-efficient and low-power computing. Through bridging these two distinct research fields, we propose a novel computing paradigm that implements the swarm intelligence with a population of coupled spiking neural oscillators in basic leaky integrate-and-fire (LIF) model. Our model behaves as a meta-heuristic searching conducted by multiple collaborative agents. In this design, the oscillating neurons serve as agents in the swarm, search for solutions in frequency coding and communicate with each other through spikes. The firing rate of each agent is adaptive to other agents with better solutions and the optimal solution is rendered as the swarm synchronization is reached. We apply the proposed method to the parameter optimization in several test objective functions and demonstrate its effectiveness and efficiency. Our new computing paradigm expands the computational power of coupled spiking neurons in the field of solving optimization problem and brings opportunities for the connection between individual intelligence and swarm intelligence.