Navigating the N-Person Prisoner's Dilemma: from the tragic valley to the collaborative hill

The N-Person Iterated Prisoners’ Dilemma (N-IPD) is an excellent environment to explore collaboration. This paper shows that the voting mechanism is crucial in determining whether sets of agents collaborate, or defect. When each agent can vote against each other agent individually, the agents become cooperative much more easily, ascending the Collaborative Hill. When the agents have only one vote each round, they tend to defect, descending into the Tragic Valley. This is shown with static decision policies, and with policies that learn using reinforcement learning. Fortunately, when agents retain enough history, they can become collaborative even with one vote each round. This voting policy difference is due to the shape of the reward space.

The research community has a great deal of knowledge about neural function and brain topology. This knowledge is by no means complete, but much of it is quite solid and is generally accepted as true. We try to take advantage of this knowledge as the basis of our models. For example, it is known that the brain is made up of neurons and these neurons connect to other neurons at places called synapses. (They may connect at other places, but most connections are synaptic.) When a pre-synaptic neuron fires, it sends activation (or inhibition) across the synapse, to the post-synaptic neuron. If the post-synaptic neuron collects enough energy it will fire.

This version of the paper has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-ma...), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-032-11402-0_19