An evaluation of Maes's bottom-up mechanism for behavior selection
Adaptive Behavior
A multivalued logic approach to integrating planning and control
Artificial Intelligence - Special volume on planning and scheduling
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Attractors in recurrent behavior networks
Attractors in recurrent behavior networks
RoboCup 2000: Robot Soccer World Cup IV
CS Freiburg: Doing the Right Thing in a Group
RoboCup 2000: Robot Soccer World Cup IV
Specifying Rational Agents with Statecharts and Utility Functions
RoboCup 2001: Robot Soccer World Cup V
RoboCup-99: Robot Soccer World Cup III
Improved Agents of the magmaFreiburg2000 Team
RoboCup 2000: Robot Soccer World Cup IV
CG '00 Revised Papers from the Second International Conference on Computers and Games
An evolutionary behavioral model for decision making
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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The problem of action selection by autonomous agents becomes increasingly difficult when acting in continuous, non-deterministic and dynamic environments pursuing multiple and possibly conflicting goals. We propose a method that exploits additional information gained from continuous states, is able to deal with unexpected situations, and takes multiple and conflicting goals into account including additional motivational aspects such as dynamic goals, which allow for situation-dependent motivational influence on the agent. Further we show some domain independent properties of this algorithm along with empirical results gained using the RoboCup simulated soccer environment.