We consider the issue of representing coalitional games in multiagent systems that exhibit externalities from coalition formation, i.e., systems in which the gain from forming a c...
Tomasz P. Michalak, Dorota Marciniak, Marcin Szamo...
In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
— In order to maintain a conflict-free environment among licensed primary users (PUs) and unlicensed secondary users (SUs) in cognitive radio networks, providing frequency and g...
Wireless sensor networks pose numerous fundamental coordination problems. For instance, in a number of application domains including homeland security, environmental monitoring an...
This paper demonstrates the applicability of reinforcement learning for first person shooter bot artificial intelligence. Reinforcement learning is a machine learning technique wh...