The aim of this research is to develop an adaptive agent based model of auction scenarios commonly used in auction theory to help understand how competitors in auctions reach equil...
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
This paper investigates the problem of estimating the value of probabilistic parameters needed for decision making in environments in which an agent, operating within a multi-agen...
The evolution of music, from random note strings to certain “pleasant” note sequences, is traced in a multi-agent computational model. A community of agents, with some musical ...
When an agent receives a query from another agent, it tries to satisfy it by building an answer based on its current knowledge. Depending on the available time or the urgency of t...