We describe our current efforts towards creating a reinforcement learner that learns both
from reinforcements provided by its environment and from human-generated advice. Our …

In this paper we are proposing an approach for coordinating a team of homogeneous agents
based on a flexible common Team Strategy as well as on the concepts of Situation Based …

Temporal difference (TD) learning methods [22] have become popular reinforcement
learning techniques in recent years. TD methods have had some experimental successes …

To promote the research of multiagent systems, several base codes have been released for
the RoboCup soccer 2D simulation community. As described herein, we present HELIOS …

This thesis describes the incremental development and main features of a synthetic multi-
agent system called UvA Trilearn 2001. UvA Trilearn 2001 is a robotic soccer simulation …

Abstract Soccer Simulation 2D League is one of the major leagues of RoboCup
competitions. In a Soccer Simulation 2D (SS2D) game, two teams of 11 players and one …

Temporal difference (TD) learning methods (Sutton & Barto 1998) have become popular
reinforcement learning techniques in recent years. TD methods, relying on function …

This team description paper presents an overview of previous work and recent research
topics of Team HELIOS2023. We have been attempting to construct a method that facilitates …

We describe Gliders2d, a base code release for Gliders, a soccer simulation team which
won the RoboCup Soccer 2D Simulation League in 2016. We trace six evolutionary steps …

A common challenge for agents in multiagent systems is trying to predict what other agents
are going to do in the future. Such knowledge can help an agent determine which of its …