Hengst, Bernhard
Online Learning and Planning in Cognitive Hierarchies
Hengst, Bernhard, Pagnucco, Maurice, Rajaratnam, David, Sammut, Claude, Thielscher, Michael
Complex robot behaviour typically requires the integration of multiple robotic and Artificial Intelligence (AI) techniques and components. Integrating such disparate components into a coherent system, while also ensuring global properties and behaviours, is a significant challenge for cognitive robotics. Using a formal framework to model the interactions between components can be an important step in dealing with this challenge. In this paper we extend an existing formal framework [Clark et al., 2016] to model complex integrated reasoning behaviours of robotic systems; from symbolic planning through to online learning of policies and transition systems. Furthermore the new framework allows for a more flexible modelling of the interactions between different reasoning components.
Termination Approximation: Continuous State Decomposition for Hierarchical Reinforcement Learning
Harris, Sean (University of New South Wales) | Hengst, Bernhard (University of New South Wales) | Pagnucco, Maurice (University of New South Wales)
This paper presents a divide-and-conquer decomposition for solving continuous state reinforcement learning problems. The contribution lies in a method for stitching together continuous state subtasks in a near-seamless manner along wide continuous boundaries. We introduce the concept of Termination Approximation where the set of subtask termination states are covered by goal sets to generate a set of subtask option policies. The approach employs hierarchical reinforcement learning methods and exploits any underlying repetition in continuous problems to allow reuse of the option policies both within a problem and across related problems. The approach is illustrated using a series of challenging racecar problems.
RoboCup-2000: The Fourth Robotic Soccer World Championships
Stone, Peter, Asada, Minoru, Balch, Tucker, D'Andrea, Raffaelo, Fujita, Masahiro, Hengst, Bernhard, Kraetzschmar, Gerhard, Lima, Pedro, Lau, Nuno, Lund, Henrik, Polani, Daniel, Scerri, Paul, Tadokoro, Satoshi, Weigel, Thilo, Wyeth, Gordon
The Fourth Robotic Soccer World Championships (RoboCup-2000) was held from 27 August to 3 September 2000 at the Melbourne Exhibition Center in Melbourne, Australia. RoboCup-2000 showed dramatic improvement over past years in each of the existing robotic soccer leagues (legged, small size, mid size, and simulation) and introduced RoboCup Jr. competitions and RoboCup Rescue and Humanoid demonstration events. The RoboCup Workshop, held in conjunction with the championships, provided a forum for the exchange of ideas and experiences among the different leagues. This article summarizes the advances seen at RoboCup-2000, including reports from the championship teams and overviews of all the RoboCup events.
RoboCup-2000: The Fourth Robotic Soccer World Championships
Stone, Peter, Asada, Minoru, Balch, Tucker, D', Andrea, Raffaelo, Fujita, Masahiro, Hengst, Bernhard, Kraetzschmar, Gerhard, Lima, Pedro, Lau, Nuno, Lund, Henrik, Polani, Daniel, Scerri, Paul, Tadokoro, Satoshi, Weigel, Thilo, Wyeth, Gordon
The Fourth Robotic Soccer World Championships (RoboCup-2000) was held from 27 August to 3 September 2000 at the Melbourne Exhibition Center in Melbourne, Australia. In total, 83 teams, consisting of about 500 people, participated in RoboCup-2000, and about 5000 spectators watched the events. RoboCup-2000 showed dramatic improvement over past years in each of the existing robotic soccer leagues (legged, small size, mid size, and simulation) and introduced RoboCup Jr. competitions and RoboCup Rescue and Humanoid demonstration events. The RoboCup Workshop, held in conjunction with the championships, provided a forum for the exchange of ideas and experiences among the different leagues. This article summarizes the advances seen at RoboCup-2000, including reports from the championship teams and overviews of all the RoboCup events.