77 citations · 354 across the 11 of their papers we have counts for
12 papers
AI for a Planet Under Pressure
Victor Galaz, Maria Schewenius, Jonathan F. Donges +26
Artificial intelligence (AI) is already driving scientific breakthroughs in a variety of research fields, ranging from the life sciences to mathematics. This raises a critical ques…
Deterministic Model of Incremental Multi-Agent Boltzmann Q-Learning: Transient Cooperation, Metastability, and Oscillations
David Goll, Jobst Heitzig, Wolfram Barfuss
Multi-Agent Reinforcement Learning involves agents that learn together in a shared environment, leading to emergent dynamics sensitive to initial conditions and parameter variation…
Perspectives on adaptive dynamical systems
Jakub Sawicki, Rico Berner, Sarah A. M. Loos +21
Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems like the powe…
Intrinsic fluctuations of reinforcement learning promote cooperation
Wolfram Barfuss, Janusz Meylahn
In this work, we ask for and answer what makes classical temporal-difference reinforcement learning with epsilon-greedy strategies cooperative. Cooperating in social dilemma situat…
Conceptualizing World-Earth System resilience: Exploring transformation pathways towards a safe and just operating space for humanity
John M. Anderies, Wolfram Barfuss, Jonathan F. Donges +3
We develop a framework within which to conceptualize World-Earth System resilience. Our notion of World-Earth System resilience emphasizes the need to move beyond the basin of attr…
Modeling the effects of environmental and perceptual uncertainty using deterministic reinforcement learning dynamics with partial observability
Wolfram Barfuss, Richard P. Mann
Assessing the systemic effects of uncertainty that arises from agents' partial observation of the true states of the world is critical for understanding a wide range of scenarios.…
Earth system modeling with endogenous and dynamic human societies: the copan:CORE open World-Earth modeling framework
Jonathan F. Donges, Jobst Heitzig, Wolfram Barfuss +9
Analysis of Earth system dynamics in the Anthropocene requires to explicitly take into account the increasing magnitude of processes operating in human societies, their cultures, e…
Deep reinforcement learning in World-Earth system models to discover sustainable management strategies
Felix M. Strnad, Wolfram Barfuss, Jonathan F. Donges +1
Increasingly complex, non-linear World-Earth system models are used for describing the dynamics of the biophysical Earth system and the socio-economic and socio-cultural World of h…
The physics of governance networks: critical transitions in contagion dynamics on multilayer adaptive networks with application to the sustainable use of renewable resources
Fabian Geier, Wolfram Barfuss, Marc Wiedermann +2
Adaptive networks are a versatile approach to model phenomena such as contagion and spreading dynamics, critical transitions and structure formation that emerge from the dynamic co…
Geometric effects in random assemblies of ellipses
Jakov Lovrić, Sara Kaliman, Wolfram Barfuß +2
Assemblies of anisotropic particles commonly appear in studies of active many-body systems. However, in two dimensions, the geometric ramifications of the finite density of such ob…
Deterministic limit of temporal difference reinforcement learning for stochastic games
Wolfram Barfuss, Jonathan F. Donges, Jürgen Kurths
Reinforcement learning in multiagent systems has been studied in the fields of economic game theory, artificial intelligence and statistical physics by developing an analytical und…
Parsimonious modeling with Information Filtering Networks
Wolfram Barfuss, Guido Previde Massara, T. Di Matteo +1
We introduce a methodology to construct parsimonious probabilistic models. This method makes use of Information Filtering Networks to produce a robust estimate of the global sparse…