In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
Multi-agent simulations aim at representing the dynamics of complex systems as resulting from multiple interactions between autonomous entities including their own perception of lo...
This paper discusses the extensions that we have made to Betty’s Brain teachable agent system to help students learn about dynamic processes in a river ecosystem. Students first ...
Physical systemsoften exhibit complexnonlinear behaviors in continuoustime at multiple temporaland spatial scales. Abstractionssimplify behavioralanalysis and help focus on domina...
Abstract. Many real world problems are given in the form of multiple measurements comprising local descriptions or tasks. We propose that a dynamical organization of a population o...