Many academic and industry professionals have called for more testing in computer science curricula. Test-driven development (TDD) has been proposed as a solution to improve testi...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
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...
We have implemented an aspect of learning and memory in the nervous system using analog electronics. Using a simple synaptic circuit we realize networks with Hebbian type adaptati...
Abstract In this paper we address the problem of simultaneous learning and coordination in multiagent Markov decision problems (MMDPs) with infinite state-spaces. We separate this ...