We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
— This paper describes a general approach for the unsupervised learning of behaviors in a behavior-based robot. The key idea is to formalize a behavior produced by a Motor Map dr...
Paolo Arena, Luigi Fortuna, Mattia Frasca, Luca Pa...
An advanced Business Game is presented in the paper, built on the methodology of System Dynamics. It can be used for cognitive learning and knowledge transmission in schools and U...
This paper extends the link between evolutionary game theory and multi-agent reinforcement learning to multistate games. In previous work, we introduced piecewise replicator dynam...
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...