Browsing by Author "Cleanthous, A."
Now showing items 1-7 of 7
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Does high firing irregularity enhance learning?
Christodoulou, Chris C.; Cleanthous, A. (2011)In this note, we demonstrate that the high firing irregularity produced by the leaky integrate-and-fire neuron with the partial somatic reset mechanism, which has been shown to be the most likely candidate to reflect the ...
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Is self-control a learned strategy employed by a reward maximizing brain?
Cleanthous, A.; Christodoulou, Chris C. (2009)
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Learning optimisation by high firing irregularity
Cleanthous, A.; Christodoulou, Chris C. (2012)In a network of leaky integrate-and-fire (LIF) neurons, we investigate the functional role of irregular spiking at high rates. Irregular spiking is produced by either employing the partial somatic reset mechanism on every ...
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Multiagent reinforcement learning with spiking and non-spiking agents in the iterated prisoner's dilemma
Vassiliades, Vassilis; Cleanthous, A.; Christodoulou, Chris C. (2009)This paper investigates Multiagent Reinforcement Learning (MARL) in a general-sum game where the payoffs' structure is such that the agents are required to exploit each other in a way that benefits all agents. The contradictory ...
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Multiagent reinforcement learning: Spiking and nonspiking agents in the Iterated Prisoner's Dilemma
Vassiliades, Vassilis; Cleanthous, A.; Christodoulou, Chris C. (2011)This paper investigates multiagent reinforcement learning (MARL) in a general-sum game where the payoffs' structure is such that the agents are required to exploit each other in a way that benefits all agents. The contradictory ...
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Self-control with spiking and non-spiking neural networks playing games
Christodoulou, Chris C.; Banfield, G.; Cleanthous, A. (2010)Self-control can be defined as choosing a large delayed reward over a small immediate reward, while precommitment is the making of a choice with the specific aim of denying oneself future choices. Humans recognise that ...
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Spiking neural networks with different reinforcement learning (RL) schemes in a multiagent setting
Christodoulou, Chris C.; Cleanthous, A. (2010)This paper investigates the effectiveness of spiking agents when trained with reinforcement learning (RL) in a challenging multiagent task. In particular, it explores learning through rewardmodulated spike-timing dependent ...