Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
We introduce the ALeRT (Action-dependent Learning Rates with Trends) algorithm that makes two modifications to the learning rate and one change to the exploration rate of traditio...
Maria Cutumisu, Duane Szafron, Michael H. Bowling,...
Abstract. This paper presents the development of a bivalve farmer agent interacting with a realistic ecological simulation system. The purpose of the farmer agent is to determine t...
Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS’s). First we review one motivation of PD theory, as the information-theoretic extens...
We study the price dynamics in a multi-agent economy consisting of buyers and competing sellers, where each seller has limited information about its competitors’ prices. In this ...