The society of mind
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
A case study in the behavior-oriented design of autonomous agents
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Adaptive Behavior
The artificial life roots of artificial intelligence
Artificial Life
The Small League RoboCup Team of the VUB AI-Lab
RoboCup-98: Robot Soccer World Cup II
Proceedings of the workshop on Deception, Fraud, and Trust in Agent Societies held during the Autonomous Agents Conference: Trust in Cyber-societies, Integrating the Human and Artificial Perspectives
The physical symbol grounding problem
Cognitive Systems Research
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Electrical energy is an important factor for a robotic agent when it tries to stay autonomously operational for some time. Monitoring this variable can provide important feedback for learning. In this paper, we present two different learning criteria based on this idea. Dealing with self-sufficient agents, i.e., agents that roughly speaking have a job to do, one criterion works over cycles of iterated "work" and "recovery". In doing so, it gives some kind of feedback of the robot's efficiency. We argue that a second criterion is needed for learning of most basic behaviors as well as in emergency situations. In these cases, fast and strong feedback, somehow comparable to pain, is necessary. For this purpose, changes in the short-term energy-consumption are monitored. Results are presented were basic behaviors of a robot in a a real-world set-up are learned using a combination of both criteria. Namely, the robot learns a set so-called couplings, i.e., combinations of simple sensor-processes with elementary effector-functions. The couplings learned enable the robot to do touch-based as well as active IR obstacle-avoidance and autonomous recharging on basis of phototaxis.