Partner selection alters opponent distributions in policy-gradient dynamics, promoting cooperation when population variance exists, with a Wiener-process stochastic extension proving a sufficient condition and stationary distribution.
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8 Pith papers cite this work, alongside 5,859 external citations. Polarity classification is still indexing.
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Institutional delays trigger instability in multi-agent systems through delayed repression, with simulations identifying reactivity to lagged signals as the destabilizing factor rather than learning.
The Perceived Cooperativity Scale and Teaming Perception Scale were developed from theory and validated across three studies to reliably measure subjective quality of human-AI cooperation.
A single spatial correlation index predicts cooperator fixation across arbitrary heterogeneous landscapes, with segregated environments enhancing and intermixed ones suppressing cooperation under weak selection.
Limited legal personhood for AI, implemented via purpose-bound operating companies within human-controlled holding structures, serves as a precautionary governance instrument that enables transparency and accountability without resolving questions of artificial consciousness.
Complexity synchronization, defined as the correlation of sliding-window MDEA and DFA scaling exponents, increases with cooperative performance in a high-interaction regime of a predator-prey multi-agent model with selfish agents and Prisoners Dilemma payoffs.
In spatial public goods games on lattices, allowing agents to reevaluate and change interaction groups promotes cooperation emergence, while high rates of group switching suppress it.
citing papers explorer
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The Dynamics of Policy Gradient in Social Dilemmas with Partner Selection
Partner selection alters opponent distributions in policy-gradient dynamics, promoting cooperation when population variance exists, with a Wiener-process stochastic extension proving a sufficient condition and stationary distribution.
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Delayed Repression and Emergent Instability in Adaptive Multi-Agent Systems
Institutional delays trigger instability in multi-agent systems through delayed repression, with simulations identifying reactivity to lagged signals as the destabilizing factor rather than learning.
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Measuring Successful Cooperation in Human-AI Teamwork: Development and Validation of the Perceived Cooperativity and Teaming Perception Scales
The Perceived Cooperativity Scale and Teaming Perception Scale were developed from theory and validated across three studies to reliably measure subjective quality of human-AI cooperation.
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Predicting success of cooperators across arbitrary heterogeneous environmental landscapes
A single spatial correlation index predicts cooperator fixation across arbitrary heterogeneous landscapes, with segregated environments enhancing and intermixed ones suppressing cooperation under weak selection.
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Precautionary Governance of Autonomous AI: Legal Personhood as Functional Instrument
Limited legal personhood for AI, implemented via purpose-bound operating companies within human-controlled holding structures, serves as a precautionary governance instrument that enables transparency and accountability without resolving questions of artificial consciousness.
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Complexity synchronization as a diagnostic and control principle for adaptive systems
Complexity synchronization, defined as the correlation of sliding-window MDEA and DFA scaling exponents, increases with cooperative performance in a high-interaction regime of a predator-prey multi-agent model with selfish agents and Prisoners Dilemma payoffs.
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Cooperation in public goods game on square lattices with agents changing interaction groups
In spatial public goods games on lattices, allowing agents to reevaluate and change interaction groups promotes cooperation emergence, while high rates of group switching suppress it.
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