A central question in artificial intelligence is how to design agents capable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by ...

Within the broad area of computational intelligence, it is of great importance to develop new computational models of human behaviour aspects. In this report we look into the recently suggested theory that neural synchronization ...

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 ...

In this letter, we propose a definition of the operational mode of a neuron, that is, whether a neuron integrates over its input or detects coincidences. We complete the range of possible operational modes by a new mode ...

In this paper, we propose new learning laws for adjusting the weights of recurrent high order neural networks (RHONN) when they are used to system identification problems. The main advantages of these learning laws over ...

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 ...

This paper investigates the distribution of four classes of neuropeptides, myomodulin, small cardioactive peptide (SCP), buccalin, and FMRFamide, in central neurons forming the network that underlies feeding behavior in ...

In the pulmonate snail Lymnaea stagnalis, FMRFamide‐like neuropeptides are encoded by a multi‐exon genomic locus which is subject to regulation at the level of mRNA splicing. We aim to understand the post‐translational ...

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 ...