It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
Imitation-based learning is a general mechanism for rapid acquisition of new behaviors in autonomous agents and robots. In this paper, we propose a new approach to learning by imit...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
In this paper we investigate the emergence of communication in competitive multi-agent systems. A competitive environment is created with two teams of agents competing in an explo...
Michelle McPartland, Stefano Nolfi, Hussein A. Abb...
The RoboCupRescue Simulation project aims at simulating large-scale disasters in order to explore coordination strategies helpful for real-life rescue missions. This can only be ac...